TY - JOUR
AU - Harinarayana,, T
AB - SUMMARY The Bhuj area, in the Kutch region of western India, is a unique intraplate seismic zone in the world where aftershock activity associated with a large magnitude earthquake (7.7 Mw Bhuj earthquake on 26 January 2001) has persisted over a decade and up till today. We studied the lithospheric resistivity structure of the Bhuj earthquake aftershock zone to gain more insight into the structure and processes influencing the generation of intraplate seismicity in broad and, in particular, to detect the deep origin and upward migration channels of fluids linked to the crustal seismicity in the area. A lithospheric resistivity model deduced from 2-D and 3-D inversions of long-period magnetotelluric (MT) data shows low resistive lithospheric mantle, which can be best explained by a combination of a small amount of interconnected melts and aqueous fluid in the upper mantle. The MT model also shows a subvertical modestly conductive channel, spatially coinciding with the Kutch Mainland Fault, which we interpret to transport fluids from the deep lithosphere to shallow crust. We infer that pore pressure buildup aids to achieve the critical stress conditions for rock failure in the weak zones, which are pre-stressed by the compressive stress regime generated by ongoing India–Eurasia collision. The fluidized zone in the upper mantle beneath the area perhaps provides continuous fluid supply, which is required to maintain the critical stress conditions within the seismogenic crust for continued seismicity. Electrical properties, Structure of the Earth, Magnetotellurics, Seismicity and tectonics 1 INTRODUCTION Intraplate seismicity, particularly with large magnitude earthquakes, has been a critical and curious topic due to its heavy impact on humanity by the loss of life and goods. A strong spatial association of (continental) intraplate seismicity with preexisting lithospheric weak zones (such as ancient rifts or failed rifts, or suture zones) has been noted, but the primary mechanism(s) responsible for seismogenesis is still elusive because of a lack of detailed seismicity, geological and geophysical data, especially to unravel the deep lithosphere structure and lithosphere-scale processes in continental intraplate seismogenic regions (Talwani 2014; Talwani 2017). The Kutch region of western India, which experienced moderate to large intraplate earthquakes during the past several decades/centuries, is one of the most seismically active intraplate regions of the world (Choudhury et al. 2018, and references therein). This region has drawn revived global attention immediately after the occurrence of large magnitude (Mw = 7.7) Bhuj earthquake on 26 January 2001, which is being continued as an unprecedented persistent intense aftershock activity around the epicentre zone (Kayal et al. 2002; Mishra & Zhao 2003; Mandal & Chadha 2008; Rodkin & Mandal 2012; Singh et al. 2012; Singh et al. 2019). The 2001 Bhuj earthquake lead to huge loss of human life and properties, and it is considered to be one of the known largest and most destructive intraplate event in the Indian subcontinent (Rastogi et al. 2014). The main rupture related to the Bhuj earthquake occurred at a depth of 23 km below the epicentre located to the north of Kutch Mainland Fault (KMF; Fig. 1) and estimated to be about 60 km east of Bhuj (23.412°N, 70.232°E). A reverse faulting with a strike-slip component fault mechanism is inferred for the main event from fault plane solution (Kayal et al. 2002), but the identification of the causative fault becomes difficult as the rupture related to the main event did not reach to the surface (Talwani & Gangopadhyay 2001; Mishra & Zhao 2003). The intense aftershock activity of the 2001 Bhuj earthquake is still continuing, therefore unique among the intraplate earthquake aftershock sequence in the world owing to the prolonged aftershock activity well beyond the typical limits of aftershocks duration (Rodkin & Mandal 2012; Choudhury et al. 2018). The ongoing seismic activity in the region makes it a natural laboratory for understanding the subsurface structure and conditions related to the genesis of intraplate seismicity in general, and particularly in ancient failed rift settings. Figure 1. Open in new tabDownload slide Map showing the major tectonic and geomorphologic features in the Kutch region of western India. Location of long-period MT (LMT) sounding data analysed in this study (solid magenta circles) and the epicentre location (red solid star) of the 26 January 2001 Bhuj earthquake along with its focal mechanism (beach-ball diagram) are shown. The right upper inset shows the location of the Kutch region. The left bottom inset shows the detailed geology of the study area, and LMT data measured at selected locations (solid magenta circles) of the broad-band MT survey sites (solid circles) studied by Abdul Azeez et al. (2018). Abbreviations: GF—Gedi Fault; IBF—Island Belt Fault; KHF—Katroll Hill Fault; KMF—Kutch Mainland Fault; KTF—Khadir Transverse Fault; MF—Manfara Fault; NWF—North Wagad Fault; SWF—South Wagad Fault; VF—Vigodi Fault. Figure 1. Open in new tabDownload slide Map showing the major tectonic and geomorphologic features in the Kutch region of western India. Location of long-period MT (LMT) sounding data analysed in this study (solid magenta circles) and the epicentre location (red solid star) of the 26 January 2001 Bhuj earthquake along with its focal mechanism (beach-ball diagram) are shown. The right upper inset shows the location of the Kutch region. The left bottom inset shows the detailed geology of the study area, and LMT data measured at selected locations (solid magenta circles) of the broad-band MT survey sites (solid circles) studied by Abdul Azeez et al. (2018). Abbreviations: GF—Gedi Fault; IBF—Island Belt Fault; KHF—Katroll Hill Fault; KMF—Kutch Mainland Fault; KTF—Khadir Transverse Fault; MF—Manfara Fault; NWF—North Wagad Fault; SWF—South Wagad Fault; VF—Vigodi Fault. Several geological and geophysical studies have been carried out to understand the tectonic structure and subsurface characteristics related to the genesis of intraplate earthquakes in the Bhuj (Kutch) region (e.g. Biswas & Khattri 2002; Kayal et al. 2002; Mishra & Zhao 2003; Biswas 2005; Mandal & Chadha 2008; Chandrasekhar et al. 2012; Rodkin & Mandal 2012; Singh et al. 2012; Kumar et al. 2017; Abdul Azeez et al. 2018; Singh et al. 2019). Crustal thickness (Moho depth) in the Bhuj seismic zone varies between ∼38 and ∼43 km (Mandal 2017, 2019; Singh et al. 2019). The reverse and strike-slip focal mechanisms shown by most of the large earthquakes in the region and the 2001 Bhuj earthquake aftershock events suggests that the seismicity in the area is mainly caused by stresses resulted from regional plate-tectonic forces (prevailing N–S compression caused by the northward movement of the Indian Plate) and local tectonic forces associated with the tectonic structures (Singh & Mandal 2018, and references therein). A few different inferences on the generation mechanism of the local tectonic forces, which cause earthquake nucleation in the area, are drawn from several studies using multidisciplinary approaches. Prominent among them are the stress accumulation in the hypocentre region due to mafic magma intrusive in the crust (Chandrasekhar & Mishra 2002; Mandal et al. 2004; Mishra et al. 2005), triggering of moderate to large earthquakes due to elevated fluid pressures (Mishra & Zhao 2003; Mandal et al. 2004; Singh et al. 2012; Mishra et al. 2014), and the generation of main shock due to intersection fault zones at depths in the Kutch rift basin (Bhatt et al. 2009). It is rather difficult to perceive a single cause for the earthquake genesis in the Bhuj region, but the presence of fluids in the crust of Bhuj region is unequivocally established by several of the geophysical studies carried out in the Kutch region and fluids role in earthquake generation either independently or in combination with other causative factors is widely accepted (Kayal et al. 2002; Mishra & Zhao 2003; Mandal et al. 2004; Chandrasekhar et al. 2012; Singh et al. 2012; Mishra et al. 2014; Kumar et al. 2017; Abdul Azeez et al. 2018). Fluids in the crust of Bhuj area have been reported by several workers, primarily using seismological and magnetotelluric (MT) data. From velocity structure and velocity perturbations of different seismic waves, presence of fluid-filled fractured rock matrix in the crust of the Bhuj earthquake epicentre zone is inferred by several studies (Kayal et al. 2002; Mishra & Zhao 2003; Mandal et al. 2004; Singh et al. 2012, 2019). The MT resistivity models showed enhanced conductivity zones in the crust, mostly coinciding with the surface trace of faults in the area, which are indicative of high fluid content in the crust (Sastry et al. 2008; Chandrasekhar et al. 2012; Mohan et al. 2015, 2018; Kumar et al. 2017; Abdul Azeez et al. 2018). Source of fluids in the crust of the region could be of mantle origin, such as aqueous fluids released during metamorphism or partial melting and aqueous fluids derived during plume activity (Mandal et al. 2004; Mandal & Chadha 2008), because mantle fluids may even penetrate into the crust through mantle reaching tectonic faults/shear zones or rifting (Pili et al. 1997). Although the presence of fluids in the crust of the Bhuj area is well mapped and marked, the possible sources in the deep lithosphere and its upward migration pathways are not well understood. The MT method is a very efficient tool to detect the presence of fluids in a variety of geological settings owing to its high sensitivity to the presence of highly conductive aqueous fluids and melt phases in rock matrix and therefore capable of imaging the distribution and migration pathways of fluids in the lithosphere (Wannamaker et al. 2002; Becken et al. 2008; Worzewski et al. 2011; McGary et al. 2014; Meqbel et al. 2014; Abdul Azeez 2016; Cordell et al. 2018). Furthermore, MT can study lithosphere architecture and delineate lithospheric scale structural changes to understand the geological and tectonic evolution of different geological settings (Malleswari et al. 2019; Kaufl et al. 2020). Several broad-band MT (0.001–1000 s) investigations have been carried out to image the electrical resistivity structure of the Bhuj area (Sastry et al. 2008; Chandrasekhar et al. 2012; Mohan et al. 2015, 2018; Kumar et al. 2017; Abdul Azeez et al. 2018). All the previous MT studies were restricted to image only the crustal resistivity structure as the broad-band signals could not penetrate deeper into the lithosphere, beyond the crust, in the thick sedimentary environment of the Kutch region (Abdul Azeez et al. 2018). Lithospheric-scale resistivity model of the Bhuj area is required to image the mantle lithosphere structure and better understand the fluids source and their upward movement paths. Since long-period MT (LMT) signals (up to 10 000 s) are required to image the upper mantle resistivity structure, particularly in regions with thick sedimentary cover as in the case of Bhuj, LMT (30–10 000 s) measurements were taken for resistivity characterization of the deep lithosphere beneath the Bhuj seismogenic zone. This paper describes a lithosphere resistivity model of this distinctive intraplate seismic zone, retrieved to gain more insight into the structure and processes influencing the generation of intraplate seismicity in broad and detect the deep origin and upward migration channel of fluids in the Bhuj seismogenic zone in particular. 2 TECTONIC SETTING OF KUTCH The Kutch region in the western territory of the Indian sub-continent (inset, Fig. 1) is recognized to be an intracontinental rift zone, which evolved as a pericratonic rift basin within the Precambrian Aravalli-Delhi mobile belt with the initial breakup of the Gondwana supercontinent into West Gondwana and East Gondwana in the Middle Jurassic (Biswas 1982; Talwani & Gangopadhyay 2001). The rift evolution phase continued through the separation of Indian Plate from the East Gondwana during Early Cretaceous and its northward motion. The counter-clockwise rotation of the Indian block widened the Kutch rift and basin formed. Significant development of the Kutch rift basin continued till the Indian Plate passed over the Reunion hot spot in Late Cretaceous and collided with the Eurasian Plate in Early Eocene (Talwani & Gangopadhyay 2001). Mesozoic sediments filled the Kutch basin prior to a series of magmatic events during the late Cretaceous period. Thus, the region evolved through complex tectonic processes, which include successive formation of half grabens towards the southern part of the basin, rift fill sedimentation till the early Cretaceous time, termination of rifting and uplift of the region in Late Cretaceous–Palaeocene/Early Eocene period as a consequence of convergent processes between India and Eurasia, post Tertiary sedimentation in the peripheral slopes of uplifted Mesozoic terrain, inversion tectonics in the post-collision stage of Indian Plate with Eurasian Plate during Mid Miocene, and Quaternary sediment deposition (Biswas 1982, 1987, 2005; Talwani & Gangopadhyay 2001). The Kutch basin with a southwesterly basin axis is bounded by Nagar-Parkar Fault (NPF) in the north and North Kathiawar Fault (NKF) in the south (Fig. 1). The Radhanpur–Barmer arch bounds the rift to the east, whereas the rift terminates in the continental shelf towards the west. The NNE–SSW Median high marks the hinge zone (Biswas 1987). The other notable faults in the region are the Katrol Hill Fault (KHF), Kutch Mainland Fault (KMF), South Wagad Fault (SWF), North Wagad Fault (NWF), Gedi Fault (GF), Island Belt Fault (IBF) and Allah Bund Fault (Fig. 1). These faults are thrust type in nature and are chiefly east–west oriented. The basin is styled by a series of uplifts, namely Kutch Mainland uplift (KMU), Wagad uplift (WU) and Island Belt uplift (IBU), which are formed by differential movements of discrete basement blocks due to N–S compression along the faults. These uplifted areas are bounded by a fault or a sharp monoclinal flexure at one side and have gently dipping peripheral plains on the other side (Biswas 1982, 1987; Biswas & Khattri 2002). During the post-collision compressive regime of the Indian Plate, the Kutch rift basin became a compressive shear zone with thrust and strike-slip movements along subparallel rift faults. The KMF along the rift axis became the principal active fault, which at present appears to be overstepped by the SWF in the eastern part of the basin (Biswas 2005). Sedimentary rocks, mostly limestone, shale and sandstones, ranging in age from Jurassic to Eocene cover Kutch region (Biswas 1987; Talwani & Gangopadhyay 2001). The Late Cretaceous and Early Palaeocene Deccan trap basaltic flows intrude and cover the Mesozoic sediments at some places (Biswas 1987). Apart from the Jurassic formation, Quaternary/Tertiary sediments occur in the plains. In addition to the master faults with a general EW trend and up-thrusts, several N–S to NE–SW and NW–SE tectonic lineaments (transverse/strike-slip faults) transects the Kutch basin (Biswas 1987; Talwani & Gangopadhyay 2001; McCalpin & Thakkar 2003). 3 MT DATA, ANALYSIS AND MODELLING 3.1 Data collection and processing Long-period MT data (∼30 to ∼10 000 s) were collected at 15 locations within the epicentral zone of the 2001 Bhuj earthquake (Fig. 1) during the Indian wintertime of 2011 and 2012 using GEOMAG02 MT systems of Research Centre Geomagnet (Ukraine). All the LMT soundings were made at places exactly coinciding with selected broad-band MT sites acquired over the study and studied earlier by Abdul Azeez et al. (2018). Simultaneous recording of all the five MT components, natural time variations in the magnetic field components of the Earth (Hx, Hy and Hz) and orthogonal components of the electric field (Ex and Ey) induced by the magnetic field variations, were made for ∼20 d at every site. The magnetic field variations were measured with fluxgate magnetometer and the associated electric field fluctuations were collected using a common cross layout configuration of pairs of non-polarized electrodes (Pb/PbCl2) with a typical dipole length of 100 m. The horizontal components of the magnetic and electric fields were measured in the geomagnetic NS (x-axis) and EW (y-axis) directions. In order to facilitate remote reference processing (Gamble et al. 1979), which could suppress the uncorrelated noise in the magnetic time-series data (by calculating the cross-power spectrum between local and remote station data) and thereby improve the quality of computed MT impedance, synchronized recording of LMT time-series data at three or four sites was executed. The recorded time-series data were processed using robust processing algorithms and computed the MT impedance tensor and magnetic field transfer function. Single-site as well as remote reference processing approaches were followed. The different approaches yielded comparable and high-quality MT impedances and magnetic field transfer function for the majority of sites. For every individual site, the best among the two different processing results was selected as the final data and considered for further analysis and modelling. Examples of MT data from three representative sites, displayed as sounding curves (apparent resistivity and phase) computed for all four components of the MT impedance tensor, are shown in Fig. 2 to illustrate the general data quality and characteristics. The sounding curves generally have smooth and very good quality responses all through the entire period range, except some minor disturbance seen in the XY component of a few sites at longest periods. The diagonal components (XX and YY) are also very well resolved. They are mostly one to two order of magnitude lower than the off-diagonal (XY and YX) components at lower periods (<1000 s), but show a significant increase in magnitude at higher periods (>1000 s). The above characteristics and the apparent divide between the two off-diagonal components hint to a complex 3-D subsurface. The off-diagonal responses show a broad resistivity increase trend with period (depth, as period is proxy for depth) prior to a tendency for resistivity decrease at longest periods, which indicates low resistive (conductive) structure at greater depths scanned by the longest periods. The above overall K-type nature (Berdichevsky & Dmitriev 2002) of the apparent resistivity curves is principally seen in the south to the central part of the profile. Figure 2. Open in new tabDownload slide Examples of long-period MT data from three representative sites (see Fig. 1 for location) to illustrate the general data quality and nature of subsurface. The MT data in the geographic coordinate system is presented as apparent resistivity and phase responses for all the four MT impedance elements. Note that the Zyx and Zxy also form the TE and TM impedances, respectively, for the east–west electrical strike direction shown by the data. Figure 2. Open in new tabDownload slide Examples of long-period MT data from three representative sites (see Fig. 1 for location) to illustrate the general data quality and nature of subsurface. The MT data in the geographic coordinate system is presented as apparent resistivity and phase responses for all the four MT impedance elements. Note that the Zyx and Zxy also form the TE and TM impedances, respectively, for the east–west electrical strike direction shown by the data. 3.2 Data analysis The MT impedance tensor obtained for each station was analysed to understand the subsurface complexity/dimensionality using the phase tensor method of Caldwell et al. (2004). The phase tensor analysis does not require any prior assumption on the subsurface dimensionality and the results are unbiased by galvanic distortion of MT data. The results are commonly demonstrated using an ellipse that is defined by one direction α and three coordinate invariants, that is the maximum phase (φmax), the minimum phase (φmin) and the skew angle (β). The subsurface dimensionality is judged from the nature of the phase tensor ellipses and skew values. The ellipse reduces to a circle, that is φmax= φmin, and β = 0 for a 1-D subsurface. In the case of 2-D subsurface, β is zero and one principal axis of the ellipse (either φmaxor φmin) aligns with the electrical strike direction. When the subsurface is 3-D, all the invariant parameters will have non-zero values and the magnitude of β will give a measure of the deviation from the 2-D case. In this case, the principal axis of the ellipse orients to the direction α–β, defining the direction of greatest inductive response and represents the closest equivalent of a strike direction (Bibby et al. 2005). In realistic situations, absolute skew angle higher than 3 (⁠|$| \beta |$| > 3°) is considered as an indication of 3-D subsurface (Caldwell et al. 2004). The phase tensor ellipses show well-defined ellipses with a consistent east–west alignment at every site and almost throughout the entire data range (Fig. 3). These results suggest that the subsurface is characterized by a dominant 2-D structure with a major conductivity direction (electrical strike) of east–west or north–south due to the inherent 90° uncertainty in strike estimation from tensor decomposition. However, between 50 s and 1000 s data range, the skew parameter values cross the border value (±3°) generally considered for 2-D behaviour of the subsurface. In this data range, many of the sites show mild (3–5°) to high (>10°) absolute skew angles, which indicate significant 3-D induction effects in these periods. Additionally, notable 3-D skew angle values are visible at several data points beyond 1000 s. Figure 3. Open in new tabDownload slide Pseudo-section of the phase tensor ellipse and skew (filled colour) computed for each data point at all the sites along the profile. Figure 3. Open in new tabDownload slide Pseudo-section of the phase tensor ellipse and skew (filled colour) computed for each data point at all the sites along the profile. A homogeneous electric strike direction expressed by the phase tensor ellipses of the whole data range implies a major 2-D subsurface structure in the area and suggests that a 2-D modelling of the data could be a valid approach to assess the subsurface geology. The subsurface dimensionality and electric strike were also studied using the widely used strike and distortion analysis algorithm of McNiece & Jones (2001), which is based on Groom & Bailey (1989) tensor decomposition approach. This method separates the effect of near-surface and regional resistivity structures in the measured MT data assuming a regional 2-D subsurface and in the case of 2-D situation it computes the regional electric strike direction, which is most consistent with the measured data. Electrical strike computed for individual data points of every site and the results are presented as statistic rose diagram of the strike for the profile in Fig. 4. A concentrated east-west (north–south, due to inherent 90° uncertainty in tensor decomposition strike) orientation of the strike values for the whole profile can be explicitly seen in the rose diagram. This is highly comparable with the phase tensor results (Fig. 4). The consistency of the strike values obtained for the whole range, from two different analyses, suggests a principal subsurface electric current flow direction (electrical strike) of east–west or north–south. Figure 4. Open in new tabDownload slide Rose plots displaying the electrical strike values computed for individual data points at all the sites along the profile using Groom and Bailey tensor decomposition (left-hand panel) and phase tensor (right-hand panel) methods. Red and blue shaded sectors represent the two possible orthogonal strike directions due to the inherent 90° ambiguity in strike determination using tensor decomposition and phase tensor methods. Figure 4. Open in new tabDownload slide Rose plots displaying the electrical strike values computed for individual data points at all the sites along the profile using Groom and Bailey tensor decomposition (left-hand panel) and phase tensor (right-hand panel) methods. Red and blue shaded sectors represent the two possible orthogonal strike directions due to the inherent 90° ambiguity in strike determination using tensor decomposition and phase tensor methods. The 90° ambiguity in electrical strike direction is solved using the east–west trend of the Kutch rift axis and all the major tectonic faults in the Kutch region. Accordingly, an east–west strike of the subsurface electrical structure is concluded and determined the 2-D MT (Transverse Electric—TE and Transverse Magnetic—TM) and tipper (magnetic field transfer function, Tzx) responses. Thus, in this case, the regional MT impedances (2-D MT data) are defined by the off-diagonal components (XY and YX). The XY component is set as the TM (electric field orthogonal to strike) and the YX component is set as the TE (electric field parallel to strike) mode data. Beyond 1000 s, the TE and TM apparent resistivity curves start to separate, and diagonal components apparent resistivity values show relative increase and attain higher values as comparable to the 2-D apparent resistivity responses (Fig. 2). These features, along with the 3-D skew values shown by phase tensor analysis, suggest that the observed MT impedance responses are the product of a 3-D subsurface structure within the scanning range of the available data range. Therefore, although a convincing strike direction that compels a 2-D modelling of the data, 3-D modelling is appropriate to derive a relevant subsurface resistivity model of the study area owing to the apparent 3-D signatures exhibited by the data. In view of the above, we decided to perform both 2-D and 3-D inversion modelling of the data so that a comparison between these models can be made before using them for geological interpretation. 3.3 2-D inversion and resistivity structure The measured 2-D MT impedances were checked for inconsistent data points, by evaluating the mutual consistency between apparent resistivity and phase data computed from impedance using D+ method (Parker 1980) included in the WinGLink software package, prior to inversion exercises. Data points that deviated largely from the D+ smooth curve (if any), obtained with a 10 per cent variation in apparent resistivity and 5 per cent in phase, were removed and not used in inversion modelling studies. The depth of penetration achieved by the highest period available for 2-D interpretation, after the above data cleaning step, was evaluated using Niblett–Bostick depth transformation technique (Jones 1983). The maximum value of the computed TE mode Bostick depths along the profile varies between 106 and 157 km and thereby showed that the TE mode data of all the sites have a consistent signal penetration beyond 100 km. The TM mode Bostick depths are mostly above 100 km (101–115 km), except two sites (02 and 03) that showed Bostick penetration depth of ∼80 km. Therefore, it can be concluded that the data used in subsurface modelling is adequate to image the crust and upper mantle electrical structures to a depth of at least 100 km. The regional MT impedance data along the profile are inverted using the non-linear conjugate gradient (NLCG) algorithm of Rodi & Mackie (2001) to deduce a smooth 2-D resistivity model that best explains the observed data set. The initial model for the inversion was constructed by discretizing a 100 Ωm half-space into a 2-D mesh with 140 columns and 84 rows. In order to accommodate the possible distortion effects in the MT data due to the Arabian Sea located at a distance of ∼60 km south of the current profile, presence of the sea was included as a fixed known resistivity structure of 0.3 Ωm in the initial model. Single mode inversion of the TE, TM and tipper (Tzx) data were performed initially with the regularization parameter (τ, which controls the trade-off between model smoothness and misfit with observed data) value of 3 and different error floor setting for the data. These preliminary inversions help to identify the observed data points having significantly large deviation from the inversion model responses (which can therefore be excluded from further inversion studies towards a final resistivity model) and decide an appropriate error floor setting for the different modes of data to generate genuine models with reasonable misfit error between the observed and modelled responses. The initial inversion tests suggested a most appropriate error floor of 20 and 5 per cent, respectively, for the apparent resistivity and phase data of both modes of MT data, and an absolute error of 0.03 for the magnetic field transfer function (tipper). Subsequently, following the L-curve approach (Hansen 1992), joint inversion of the TE, TM and Tzx data was carried out for different values of τ to determine the optimal τ value for the data set. The L-curve analysis found an optimum value of τ = 3 (Fig. S1) for the data set to generate a smooth model with a reasonable misfit. Final inversions were carried by jointly inverting the TE, TM and tipper data (as models from joint inversion of all the responses can give a comprehensive resistivity image of the subsurface, e.g. Unsworth et al. 1999) using the optimal τ value 3, without any additional horizontal as well as vertical smoothing and the appropriate error floors determined for different data components. The higher error floor assigned to the apparent resistivity data (20 per cent) over the phase (5 per cent) down-weights the apparent resistivity during the inversion and could overcome the possible static shift effects in MT data (Ogawa 2002). Additionally, visual inspection of the sounding curves at all the sites for any large-scale static shift effects was carried out and found that the TM apparent resistivity curve at site L04 has a decade downward shift as compared to the neighbouring sites TM response, which could be due to static shift from near surface heterogeneity. In order to verify this, the LMT response of L04 was compared with the BBMT data (Abdul Azeez et al. 2018) at the same location. The comparison showed a significant deviation of the TM (XY) apparent resistivity responses and a clear downshifting of the long-period TM apparent resistivity responses when compared to the corresponding broad-band range responses (Fig. S2). Therefore, the long-period TM apparent resistivity curve was shifted upwards to the level of corresponding broad-band apparent resistivity curve, which also match with the TM responses of nearby LMT sites, to remove the significant static shift in the TM mode of L04 site prior to its use in the final inversions. The inversion yielded a smooth resistivity model with very good fit between the modelled and measured 2-D MT responses and an estimated RMS misfit error of 1.035 after 100 iterations. The inherent non-uniqueness in the inversion was tested by starting the inversion from different half-space values (10, 500 and 1000 Ωm) and also by varying the inversion parameters. All these joint inversions produced almost identical models and showed essentially similar resistivity features. Fig. 5 presents the preferred resistivity model derived from the simultaneous inversion of TE, TM, and tipper data. The site-by-site RMS misfit values along the profile (upper panel, Fig. 5) show adequate fitting of data at individual sites along the profile. The very good agreement between the observed and model responses are illustrated in the supplementary information Figs S3 and S4. A relatively poorer fit between observed and modelled tipper responses is noted at some of the sites, particularly for the southern sites. The phase data, which was emphasized more during the inversions, shows an excellent match at every site when compared to the apparent resistivity data. Figure 5. Open in new tabDownload slide 2-D lithospheric resistivity model (lower panel) and RMS misfit between the observed and model responses at individual sites (upper panel). Key resistivity structures identified in the model are labelled. The seismic Moho (solid grey line) and LAB (solid pink line) depths modelled by Mandal (2019) are marked. Dashed line in the upper panel shows the profile RMS misfit. Figure 5. Open in new tabDownload slide 2-D lithospheric resistivity model (lower panel) and RMS misfit between the observed and model responses at individual sites (upper panel). Key resistivity structures identified in the model are labelled. The seismic Moho (solid grey line) and LAB (solid pink line) depths modelled by Mandal (2019) are marked. Dashed line in the upper panel shows the profile RMS misfit. The resistivity model shows two principal conductive features, a subvertical low-resistive crustal anomaly C1 (∼50–200 Ωm) underneath the area between L04 and L03 that extends deep into the upper mantle and connects to an upper mantle conductive (low-resistive) zone C2 (resistivity ranges from ∼100 to ∼200 Ωm) appearing along the profile (Fig. 5). Resistive zones R1 and R2, which bounds the low-resistive anomaly C1, characterize a major part of the lithosphere section. The robustness of the observed conductive anomalies and resistive structures was verified through non-linear sensitivity analysis in which the conductive feature under test was replaced with a resistive structure and vice versa. In the case of conductive features, the actual low resistivity values of these features were replaced individually with higher resistivity of 1000 Ωm shown by the resistive parts of the lithosphere and computed the MT and tipper responses of the modified 2-D resistivity models. Likewise, the resistive structures in the model were changed to conductive (100 Ωm) one by one, and the respective altered model responses were calculated. The measured, preferred model and altered model responses were compared for any recognizable changes between them, importantly between the preferred model and altered model responses. In the case of the conductive feature C1, the altered model RMS misfit error (1.159) showed a nominal increase over the original model RMS misfit value of 1.035. The comparison of the data at individual sites showed small, but distinguishable, difference between the original and altered model responses, vitally in phase data ranging from 80 to 400 s, at sites located to the north of C1 structure (Fig. 6a). The above deviation of the altered model response from the original model response is also reflected in the individual site RMS misfit, which shows value appreciably higher than the one obtained for the original model (Fig. 6a). The sensitivity test for the feature C2 also showed somewhat similar results as seen for the C1 feature. In this case, the discrepancy between the original and altered model is evident in both TE and TM phases (Fig. 6a). Figure 6. Open in new tabDownload slide Open in new tabDownload slide Open in new tabDownload slide (a) Results of non-linear forward sensitivity test performed for the conductive features C1 and C2 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for selected sites. (b) Results of non-linear forward sensitivity test performed for the resistive features R1 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for selected sites. (c) Results of non-linear forward sensitivity test performed for the resistive features R2 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for sites located over the feature. Figure 6. Open in new tabDownload slide Open in new tabDownload slide Open in new tabDownload slide (a) Results of non-linear forward sensitivity test performed for the conductive features C1 and C2 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for selected sites. (b) Results of non-linear forward sensitivity test performed for the resistive features R1 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for selected sites. (c) Results of non-linear forward sensitivity test performed for the resistive features R2 of the final 2-D MT model. The observed, original model and altered model 2-D MT and tipper data are presented for sites located over the feature. A robustness test for the resistive feature R1 indicated significant changes in the tipper data computed for original and altered models (Fig. 6b). The MT responses showed a relatively negligible difference between the two models. The sensitivity test for the resistive structure R2 showed a huge difference between the original model and altered model TM responses, importantly in the phase data below 500 s (Fig. 6c). All the above sensitivity results suggest that the conductive and resistive structures imaged by 2-D inversion are required to explain the measured 2-D MT and tipper data simultaneously. 3.4 3-D inversion and resistivity structure We used the parallelized version of nonlinear conjugate gradient (NLCG) 3-D MT data inversion algorithm of ModEM modular system (Kelbert et al. 2014), which has provision to invert any combination of MT impedance tensor and tipper responses, to generate 3-D resistivity model from the present data set. We used a model space discretized into 78 (X-direction) × 70 (Y-direction) × 63 (Z-direction) mesh blocks in which the central part encompassing the MT sites divided into 40 (X-direction) × 32 (Y-direction) equal-sized blocks with a uniform dimension of 1.5 km in X and Y-directions. This created several cells between MT sites, which would allow the inversion to retrieve small scale resistivity structure between sites. The core part of the model was padded using 19 cells in each side with an increasing factor of 1.3 in all directions. The top layer in the model was given a value of 20 m thickness, which increased by a factor of 1.15 in the vertical (Z) direction to ∼116-km-thick last (63rd) layer that extends till a depth of 889 km. The total volume of the 3-D model space cube amounted to 1947 km × 1932 km × 889 km, which covers a volume several times larger than volume determined by the maximum penetration depth shown by the data and thus appropriate to satisfy the boundary conditions (and stabilize the inversion) for accurate computation of the subsurface resistivity changes. We selected all the MT sites and utilized 29 periods from 28 to 10 000 s (same as the data included in the 2-D inversion exercise) in the 3-D inversion. Inversion of the full impedance tensor and tipper responses were carried out from an initial model space consisting of the land region and the Arabian ocean in the vicinity of the study area. The ocean was incorporated into the model space using bathymetry data from ETOPO1 global relief model (Amante and Eakins 2009) with ocean water resistivity of 0.3 Ωm. The regularization parameter (λ) in the inversion, which controls the compromise between the model smoothness and the data fitting, was set into an adaptive mode during the inversion process with an initial λ of 10 and its decrease by a factor of 10 whenever the differences between the data misfits of two successive iterations is below 0.01. A model covariance of 0.2 in all three spatial directions (X, Y and Z) with two passes was opted before deciding the most desirable covariance value for the data set. We assigned a standard deviation error floor of 10 per cent |$\sqrt {| {{Z_{xy}}{Z_{yx}}} |} $| to all the impedances and 3 per cent to tipper data. Initially, inversions run for different land resistivity values (1, 10, 30, 50, 100, 300 and 500 Ωm) to determine an appropriate initial model space resistivity value. The test inversions showed that an initial model with 50 Ωm land resistivity is most suitable for the data set due to smallest initial RMS misfit value shown by this initial model space and quickest convergence (lesser/minimum number of iterations taken for convergence) producing a final iteration model with lowest RMS misfit error as compared to the other initial model resistivity values. Subsequently, the most suitable model covariance for the present data set was studied by performing inversion for different covariance values, namely 0.05, 0.1 and 0.3, using the 50 Ωm starting model. The study showed that covariance of 0.1 in all three directions give maximum convergence and model with lowest RMS misfit. Furthermore, inversions exercised with different error floor settings, which suggested that a standard deviation error of 5 per cent |$\sqrt {| {{Z_{xy}}{Z_{yx}}} |} $| for the off-diagonal impedance, 10 per cent |$\sqrt {| {{Z_{xy}}{Z_{yx}}} |} $| for diagonal impedance, and 3 per cent to tipper responses. Accordingly, the final model was derived using the above error floor setting from the 50 Ωm starting model using a covariance value of 0.1 in all three directions. The final inversion model obtained yielded a normalized RMS misfit of 1.556. Overall, an ideal match between the observed and modelled data is seen with MT as well as the tipper components at all the sites, except a relatively inferior data fit noted for three sites in the northern end of the profile (see Fig. S5). The RMS misfit estimated for the individual sites (Fig. 7g) clearly illustrates the above results and shows comparatively higher RMS values at the northernmost locations. In general, the off-diagonal MT impedance and tipper data are better fitted by the 3-D model than the diagonal MT impedances. Figure 7. Open in new tabDownload slide Depth slices of the 3-D resistivity model (a–f). The tectonic features in the study area and epicentre of the 2001 Bhuj earthquake are also shown over the resistivity depth sections. Notable resistivity structures in the model are marked. The RMS misfit between the observed and 3-D model responses at individual sites are presented in Fig. 7(g). Solid blue line in Fig. 7(h) shows the line along which vertical cross-section of the 3-D model (Fig. 8) is retrieved. Figure 7. Open in new tabDownload slide Depth slices of the 3-D resistivity model (a–f). The tectonic features in the study area and epicentre of the 2001 Bhuj earthquake are also shown over the resistivity depth sections. Notable resistivity structures in the model are marked. The RMS misfit between the observed and 3-D model responses at individual sites are presented in Fig. 7(g). Solid blue line in Fig. 7(h) shows the line along which vertical cross-section of the 3-D model (Fig. 8) is retrieved. The preferred 3-D resistivity model is displayed in Figs 7 and 8 as depth slices and vertical cross-section along the MT profile direction (see Fig. 7), respectively. The model exhibits a near-vertical low-resistive (∼50–150 Ωm) crustal feature (C1) at the southern edge of the profile (below site L05), which cuts through a resistive crust to join with a (moderately) conductive upper mantle zone C2 (∼50–<100 Ωm) under the study area. The model broadly shows resistive rock matrix at mid-lower crustal depth range. The low-resistive C1 anomaly disperses the resistive crust into two notable resistive (200–500 Ωm) crustal features, namely R1 and R2 as marked in Figs 7 and 8. Before making any inferences based on the observed resistivity features of the 3-D model, the genuineness of these features is verified through non-linear sensitivity tests in a similar way as performed for the 2-D model. Here, the conductive features C1 and C2 were replaced individually with the higher resistivity observed for the nearby crustal section. It can be seen from the results of the sensitivity tests illustrated in Fig. 9(a) that altered model responses have notable changes from the original model responses. This is very clear in the results obtained for C2 feature, which shows huge discrepancies between the original model and altered model responses, both in MT and tipper data, at sites over the feature and close to it. In the case of C1, an apparent mismatch between original and altered model responses is visible at sites in the southern half of the MT coverage, mainly from site L05 to site L01. The above results indicate that the conductive features C1 and C2 are indispensable resistivity structures of the derived 3-D model to explain the observed MT and tipper data set satisfactorily. Similarly, the presence of resistive features R1 and R2 were tested by replacing them separately with the conductive half-space resistivity value (50 Ωm) used for the final inversion. The computed responses of the altered model show significant deviation from the original model responses (Figs 9b and S6), which illustrate that the resistive structures imaged by 3-D inversion are robust and required features in the 3-D model. Figure 8. Open in new tabDownload slide Vertical resistivity section of the 3-D model obtained using LMT data (middle panel) along a line shown in Fig. 7(h). The 2-D resistivity section generated through 2-D inversion of LMT data (bottom panel) and crustal resistivity model of the area from 3-D inversion BBMT data (upper panel) carried out by Abdul Azeez et al. (2018) are also shown for comparison. Major resistivity features of the 2-D and 3-D models obtained from this study are labelled. A low-resistive anomaly appeared in the 3-D crustal section of Abdul Azeez et al. (2018), which is comparable with C1 feature in the present 3-D model, is highlighted using red line. The seismic Moho (solid grey line) and LAB (black line) depths modelled by Mandal (2019) are also marked. Figure 8. Open in new tabDownload slide Vertical resistivity section of the 3-D model obtained using LMT data (middle panel) along a line shown in Fig. 7(h). The 2-D resistivity section generated through 2-D inversion of LMT data (bottom panel) and crustal resistivity model of the area from 3-D inversion BBMT data (upper panel) carried out by Abdul Azeez et al. (2018) are also shown for comparison. Major resistivity features of the 2-D and 3-D models obtained from this study are labelled. A low-resistive anomaly appeared in the 3-D crustal section of Abdul Azeez et al. (2018), which is comparable with C1 feature in the present 3-D model, is highlighted using red line. The seismic Moho (solid grey line) and LAB (black line) depths modelled by Mandal (2019) are also marked. Figure 9. Open in new tabDownload slide (a) Results of non-linear forward sensitivity test performed for the conductive features C1 (top row) and C2 (bottom row) in the 3-D model. The observed, original model and altered model 3-D MT and tipper data are presented for selected sites. Note that tipper component that shows major difference between original and altered model responses is only presented. (b) Results of non-linear forward sensitivity test performed for the resistive structures R1 (top row) and R2 (bottom row) in the 3-D model. The observed, original model and altered model 3-D MT and tipper data are presented for selected sites. Note that tipper component that shows major difference between original and altered model responses is only presented. Figure 9. Open in new tabDownload slide (a) Results of non-linear forward sensitivity test performed for the conductive features C1 (top row) and C2 (bottom row) in the 3-D model. The observed, original model and altered model 3-D MT and tipper data are presented for selected sites. Note that tipper component that shows major difference between original and altered model responses is only presented. (b) Results of non-linear forward sensitivity test performed for the resistive structures R1 (top row) and R2 (bottom row) in the 3-D model. The observed, original model and altered model 3-D MT and tipper data are presented for selected sites. Note that tipper component that shows major difference between original and altered model responses is only presented. Figure 9. Open in new tabDownload slide (Continued.) Figure 9. Open in new tabDownload slide (Continued.) 3.5 Comparison between 2-D and 3-D resistivity models The resistivity picture brought out by the two different inversion approaches, 2-D and 3-D, are comparable and show a broad similarity of major resistivity features imaged in the models (Fig. 8). The notable difference between 2-D and 3-D structure is the change in position of the low-resistive crustal anomaly C1. In the 2-D model, this feature appears between sites L04 and C03 coinciding roughly with the SWF marked in the area. However, the 3-D model shows similar near-vertical low-resistivity anomaly beneath the southernmost site (L05) and correlates well with the surface position of KMF, the major fault structure in the area that forms the axis of the Kutch rift basin. A similar low resistive feature through the resistive crust, at same location as seen in the 3-D model, can be seen in the 3-D MT imaging of the crust carried out by Abdul Azeez et al. (2018) using BBMT data (Fig. 8). The crustal sections obtained from the individual 3-D studies of BBMT and LMT data show comparable results, though the two studies used two different 3-D inversion algorithms and data components. 3-D inversion can produce a more realistic subsurface picture as it provides a reasonable picture of the resistivity structures in the neighbourhood of the site coverage (Siripunvaraporn et al. 2005; Patro & Egbert 2011) and thus could yield more realistic images of off-profile structures, particularly when full MT impedance and tipper responses are used (Campanyà et al. 2018). The change in position of the C1 anomaly in the 2-D and 3-D models could be due to the inability of 2-D approach to accurately map off-profile structures. Therefore, the 3-D resistivity model is preferred over the 2-D model, and the resistivity features common in the two models are used in interpretation to derive conclusions about the subsurface geological conditions in the area. 4 INTERPRETATION AND DISCUSSION The MT imaging shows that the upper mantle below the Bhuj seismic zone is characterized by enhanced conductivity as against a high resistivity commonly anticipated for a normal (depleted) continental lithosphere mantle. The joint inversion of P-receiver functions and surface waves showed mean lithosphere thickness values varying between 84 and 103 at different locations over the Kutch rift zone (Mandal 2019), which suggests that the observed conductive anomalies are largely within the lithosphere. Conductive mantle lithosphere occurs below the study area, while the crustal (mid-lower crust) portion of the lithosphere appears to be chiefly resistive (Fig. 8). Presence of conductive/low-resistive zones in the continental lithosphere are a strong evidence of lithosphere that has undergone substantial deformation and/or fluid and magmatic flux through various geodynamic or tectonic processes (Worzewski et al. 2011; Unsworth & Rondenay 2013; Meqbel et al. 2014; Abdul Azeez et al. 2015; Yin et al. 2017). In most cases, enhanced conductivity/low-resistivity of the deep crust and mantle lithosphere signals to geodynamic or tectonic processes that are either currently operational or operated during the recent geological past in the area (Unsworth & Rondenay 2013; Meqbel et al. 2014; Danda et al. 2017; Yin et al. 2017; Comeau et al. 2018; Vijaya Kumar et al. 2018). The Mesozoic–Cenozoic tectonic history of the Indian Plate has been spectacular ever since the beginning of the fragmentation of the Gondwana supercontinent into the West Gondwana (Africa and south America) and the East Gondwana (Antarctica, Australia, New Zealand, Madagascar, Seychelles, India and Sri Lanka) in the Early Jurassic (Chatterjee et al. 2013; Bhattacharya & Yatheesh 2015). Subsequently, the greater India (conjoined India-Madagascar-Seychelles-Sri Lanka) continental block separated from the east Gondwana and made an unusually rapid northward migration away from conjoined Antarctica-Australia (Kumar et al. 2007) prior to its present-day collision with Eurasia that commenced from the Late Palaeocene–Middle Miocene time (Gibbons et al. 2015, and references therein). During the northward journey, the greater India was afflicted by two more major rift episodes, under the influence of different mantle plumes, that shaped the current western continental margin of India and significantly influenced the nature of the Indian continental lithosphere overall, particularly close to the western margin (Raval & Veeraswamy 2000; Kumar et al. 2007; Abdul Azeez et al. 2015; Sharma et al. 2018; Vijaya Kumar et al. 2018; Singh et al. 2019). The first rift event between India and Madagascar occurred during Mid Cretaceous (∼88 Ma) under the influence of Marion mantle plume (Storey et al. 1995) and the second rifting process that separated Seychelles from India at ∼63.4 Ma (Collier et al. 2008) during the passage of India Plate over the Reunion mantle plume, which are manifested on the surface as volcanic dykes and basaltic magma flows in different parts of the Indian subcontinent (Anil Courtillot et al. 1986; White & McKenzie 1989; Kumar et al. 2001). These Cretaceous-Tertiary riftings occurred along the major Precambrian tectonic trends in the Indian subcontinent (NNW–SSE Dharwar trend, the NE–SW Aravalli trend and the ENE–WSW Satpura trend) as the weakened lithosphere of these deformed tectonic structures could facilitate the rifting process (e.g. Raval & Veeraswamy 2000; Bhattacharya & Yatheesh 2015). Three intracontinental rift basins, that is Kutch, Cambay and Narmada, were also formed by the reactivation of the primordial tectonic faults associated with the Precambrian trends during the rift events that lead to the Gondwana supercontinent disintegration. The Kutch rift basin, situated at the western margin of the Indian continent, opened during Jurassic–Early Cretaceous along the Aravalli trend and was aborted in Late Cretaceous (Biswas 1987; Bhattacharya & Yatheesh 2015), and acted as one of the eruption channels for Reunion plume that created the Deccan flood basalt province on western and central India (e.g. Raval & Veeraswamy 2000; Paul et al. 2008). The Reunion plume intensely affected the northwestern margin and adjoining continental parts of India and induced lithosphere scale modifications (through thermal perturbations and extensive magma plumping) as the Indian Plate moved northwards over the plume (Raval & Veeraswamy 2000; Patro & Sarma 2016; Danda et al. 2017; Sharma et al. 2018; Vijaya Kumar et al. 2018; Mandal 2019; Singh et al. 2019). Given the above tectonic history of the Kutch region and lack of any active plate tectonic processes at present under the Kutch region, it is highly sensible to suggest that the observed upper mantle conductive zone underneath the Kutch (Bhuj) seismic zone might be a manifestation of the lithosphere stretching associated with Kutch rift opening during the Jurassic period, Cretaceous–Tertiary asthenosphere upwelling (Reunion plume) and coeval interaction between the lithospheric mantle and asthenospheric mantle material (magma) injected into the weakened lithosphere. Seismic velocity images of the NW Indian region have shown low Vp and Vs in the upper mantle beneath the Kutch–Saurashtra and its neighbouring regions, which are presumed to be generated from the thermal and compositional effects of plume–lithosphere interaction and related volcanism (Kennett & Widiyantoro 1999; Sharma et al. 2018; Mandal 2019, and references therein; Singh et al. 2019). Petrology, geochemistry and palaeomagnetic studies of magmatic rocks of Kutch basin suggested that they were generated due to the impact of the Reunion plume on the Kutch lithosphere under extensional setting (Peng & Mahoney 1995; Karmalkar et al. 2005; Paul et al. 2008). Resistivity structure of the deep lithosphere around the Kutch region, namely Cambay rift basin and Saurashtra peninsula, studied using long-period MT data demonstrated conductive upper mantle zones, which are suggested to be produced by plume (Reunion)–lithosphere interaction (Danda et al. 2017; Vijaya Kumar et al. 2018). 4.1 Evidence for conductive upper mantle (C2) A mantle plume, low-density high-temperature rock material that originates in the deep mantle, transport the deep mantle material (fertile peridotite magmas rich in Mg and Fe) into the lithosphere during its ascend and onto the surface environment as it breaches through the lithosphere (Humphreys & Schmandt 2011). The plume head impingement at the base of the continental lithosphere can cause domal uplift, lithosphere delamination, lithospheric thinning due to extensional stress fields that result in either narrow or wide rifts and/or continental breakup (Buck 1991; Condie 2001; Burov et al. 2007; Koptev et al. 2015). Melts are produced as a result of both adiabatic decompression of the rising plume head and heating the base of the lithosphere by the plume thermal anomaly, leading to both plume-derived and mantle-lithosphere melts. Magmatic aqueous fluids enriched with H2O, CO2 and sulfides are released during magma decompression (Luth 2003; Yardley & Bodnar 2014). Melt and aqueous fluids eventually would migrate (vertically as well as laterally) into different parts of the lithosphere and extrude onto the surface through active continental rifting (mostly) and/or by taking the pre-existing weak lithosphere zones as pathways to form large continental flood basaltic cover on the Earth surface (Dunbar & Sawyer 1989; Sleep et al. 2002; Corti 2009; Koptev et al. 2015). Thus, plume-lithosphere interaction brings significant physical and chemical changes in the lithosphere by plume head heating and pervasive percolation of fluids (melts and aqueous/magmatic fluids) through porous channels in the lithosphere over a horizontal distance for hundreds of kilometres (Tang et al. 2013 and references therein). All these lead to rejuvenation (refertilization) of the continental lithosphere through enrichment and/or metasomatism by the action of plume-derived melts and aqueous fluids (Griffin et al. 2013; Selway 2014). Melt and magmatic fluids (aqueous fluids) are highly conductive, typically orders of magnitude more conductive than crystalline host rock (Jones 1992; Selway 2014). Hence the presence of interconnected melt and fluids phases in an otherwise high resistive host medium could dramatically reduce the bulk resistivity of the host medium, depending upon the degree of their volume percentage and interconnection, and produce enhanced conductivity zones like C2 seen in the present study (Selway 2014). Also, the interaction of mantle-derived melts and associated fluid systems with the host rock could lead to precipitation of significant quantities of highly conductive graphite and sulfide mineralization, through hydrothermal alteration, and thus cause conductivity enhancement in the lithosphere (Jones 1992; Wang et al. 2013; Selway 2014). The presence of alkaline rocks generated by partial melting of CO2-rich Iherzholite reported from Kutch rift (Sen et al. 2009) hint at graphite formation in the mantle lithosphere. But, the representative lithospheric geotherm computed for the Bhuj region (Pandey et al. 2017) that indicates higher temperature conditions (>800 °C) at upper mantle depths of 60 km and above negates graphite presence as conductivity enhancing mechanism as graphite films on grain boundaries is not stable at high temperatures over 730 °C (Yoshino & Noritake 2011). The presence of sulfides in the mantle can also be excepted from the list of possible agents for the observed enhanced mantle conductivity, since the oxygen fugacity of the mantle is beyond the stability field of most sulfides (Frost & McCammon 2008). Consequently, melt and/or aqueous fluids are the most realistic explanation for the conductive upper mantle zone occurring beneath the Bhuj area. No direct heat flow measurement data is yet available for the Kutch region; however, a moderate surface heat flow of 61.3 mW m–2 (Vedanti et al. 2011) with a high mantle heat flow component of 43 mW m–2 (Pandey et al. 2017) are predicted for the Kutch seismogenic zone through indirect approaches. The predicted thermal regime of the Kutch lithosphere does not suggest any active plume–lithosphere interaction (owing to the moderate surface heat flow), but indicate warm upper mantle conditions from the higher mantle heat flow contribution towards the moderate surface heat flow. Thus, the low resistivity and excess heat conditions in the mantle indicates the existence of hot and wet mantle materials, that is high temperature fluids. The hot fluids (melts and aqueous thermal fluids) may certainly have generated due to the most recent tectonothermal event operated in the region, namely the Reunion plume–lithosphere interaction during Late Cretaceous to Early Tertiary times. The MT result is consistent with the presence of upper mantle low velocity zones below the Bhuj seismogenic zone, imaged by seismic receiver function and tomographic studies, which were explained by the presence of partial melts and/or magma fluids in the mantle rock matrix, produced from the Reunion plume-lithosphere episode at ∼65 Ma (Mandal 2017; Mandal 2019; Singh et al. 2019). Similar upper mantle conductive regions are imaged by MT studies across the neighbouring regions of Kutch, namely the Cambay rift zone to the east (Danda et al. 2017) and Saurashtra region in the south (Vijaya Kumar et al. 2018) of Kutch, which are attributed to the presence of melt and aqueous fluids derived through Reunion plume–lithosphere interaction. Geochemical analysis of ultramafic xenoliths entrained in the alkaline rocks of Kutch indicated metasomatism in the SCLM of the region caused by infiltrating fluids derived from rising mantle plume material (Karmalkar et al. 2005). 4.2 Evaluation of fluid content and nature Since fluid is found to be the most plausible cause of conductive nature of the upper mantle beneath the intraplate seismogenic zone of Bhuj, it is interesting to evaluate the volume percentage and nature (melt or aqueous) of fluid present in the upper mantle as several studies inferred the role of fluid, sourced from the mantle, in the ongoing intraplate crustal seismicity of the area. It is rather difficult to have a distinct quantification of melt and aqueous fluid components contribution for the observed low resistivity mantle zone. However, an evaluation of contribution limits of each fluid component can be made assuming that the low-resistivity anomaly detected in the mantle is solely by one of the two components. Therefore, we separately computed the possible volume percentage contribution of water (as aqueous fluid is chiefly water rich) and melt towards the upper mantle low resistivity. We followed the approach of Wang et al. (2006), who studied the effect of water content on the resistivity of olivine aggregates at high temperature and pressure, to assess the relation between water content and effective resistivity of the upper mantle rock matrix. Theoretical curve was constructed from the bulk resistivity values computed for a range of water content using an average value of different constants in Wang et al. (2006) formula. In this study, the calculations were made for two different temperature values, 990 and 1280 °C, that correspond to the predicted temperature change from 60 to 80 km depth under the Bhuj upper mantle (see Fig. S7, Pandey et al. 2017). The results shown in Fig. 10(a) indicates that water content ranging from 0.002 to 0.017 wt per cent could produce the observed upper mantle low resistivity (conductive mantle lithosphere) that lies between ∼50 and ∼100 Ωm. Figure 10. Open in new tabDownload slide Bulk resistivity computed assuming water (a) and melt (b) as the resistivity lowering agent in the upper mantle zone beneath the Bhuj seismic zone. The black dashed lines represent the range of resistivity (∼50–∼100 Ωm) for the upper mantle conductive zone (feature C2 in Fig. 8). Resistivity as a function of water content (a) was calculated following Wang et al. (2006). Two-phase mixing models of modified Archie's law (Glover et al. 2000) and Hashin & Shtrikman (1962) for two conductive phases were utilized to construct the theoretical curves illustrating the relation between bulk resistivity and melt fraction volume (b) in the upper mantle rock matrix. The shaded parts indicate the possible range of water content (green) and/or melt fraction (grey) to produce the observed low-resistivity of the mantle lithosphere. Figure 10. Open in new tabDownload slide Bulk resistivity computed assuming water (a) and melt (b) as the resistivity lowering agent in the upper mantle zone beneath the Bhuj seismic zone. The black dashed lines represent the range of resistivity (∼50–∼100 Ωm) for the upper mantle conductive zone (feature C2 in Fig. 8). Resistivity as a function of water content (a) was calculated following Wang et al. (2006). Two-phase mixing models of modified Archie's law (Glover et al. 2000) and Hashin & Shtrikman (1962) for two conductive phases were utilized to construct the theoretical curves illustrating the relation between bulk resistivity and melt fraction volume (b) in the upper mantle rock matrix. The shaded parts indicate the possible range of water content (green) and/or melt fraction (grey) to produce the observed low-resistivity of the mantle lithosphere. The melt fraction required to produce enhanced conductivity of the lithospheric mantle was computed using modified Archie's law (Glover et al. 2000) and Hashin and Shtrikman lower bound (Hashin & Shtrikman 1962) that utilize two-phase mixing models to account for two conductive phases presence in the mantle, that is the mantle rock matrix and melt. In the computations, we assumed hydrous basaltic melt phase conductivity (inverse of resistivity) of 5 S m–1 (i.e. 0.2 Ωm resistivity) as the typical electrical conductivity of melts range from 1 to 10 S m–1 (Tyburczy & Waff 1983). In consideration of the mantle temperature beneath Bhuj, ∼1000–∼1300 ° C between 60 and 80 km as predicted by Pandey et al. (2017), rock matrix resistivity value of 2000 Ωm is appropriate in accordance with SEO3 model (Constable 2006) for dry olivine. The value of the cementation factor (m), that describes the degree of interconnection of the melt phase, for melt estimation using modified Archie's law was obtained from 10 Grotenhuis et al. (2005). They advocated, on the basis of laboratory studies in olivine rocks, that the olivine melts are well described by Archie's law with m = 1.3. Bulk resistivity computed for a range of melt fraction using the two mixing laws and plotted as a function of melt fraction (Fig. 10b). According to the computed theoretical lines in Fig. 10(b), the resistivity range of the C2 feature could have a melt fraction range of 0.4–1.4 per cent. Aqueous fluids may remain/reside in the lithosphere for about 100 Ma after the cessation of tectonic activity without any mechanism of recharge (Bailey 1990; Thompson & Connelly 1990). The maximum fluid percentage inferred from the observed low resistivity (∼1.4 per cent) is incompatible with the petrological inference that fluid storage beyond 0.1 per cent is implausible over geological time spans (Yardley & Valley 2000). Mandal (2019) inferred the presence of carbonatite partial melts in the asthenosphere below the Bhuj earthquake zone, based on a marked reduction in shear velocity (2.4–5.8 per cent) at the lithosphere–asthenosphere boundary below the Kutch rift zone, which could be representing the imprints of earlier episodes of magmatism (syn-rift and 65 Ma Deccan volcanism) occurred in the region (Kennett & Widiyantoro 1999). It is possible that the water-rich fluids from deep mantle penetrate into the weak lithospheric zone under Bhuj, therefore still getting recharged, as the region is being tectonically vibrant. The computed lithospheric mantle geotherm gives temperature values ranging from ∼850 to ∼1280 °C in the depth range of 50–80 km (Fig. S7, Pandey et al. 2017), which indicates that hydrous/wet melting is possible in the upper mantle (onset of wet partial melting occurs around 650 °C; Lebedev & Khitarov 1964), and even dry melting is feasible beyond 70 km depths as temperature condition favorable for melting of dry rocks (∼1200 °C; Lebedev & Khitarov 1964) exist at >70 km depths under the Bhuj area (Pandey et al. 2017). Therefore, both hydrous and melt phases are possible in the upper mantle beneath Bhuj. The seismic tomography shows 2–6 per cent reduction in P- and S-wave velocities, that is –2 to –6 per cent velocity anomalies (Mandal 2019; Singh et al. 2019), in the upper mantle corresponding to the low resistivity zone imaged by MT. Chantel et al. (2016) showed that very small amounts of melt (<1 per cent) have a significant effect on seismic velocities of upper mantle materials, even ∼0.2 per cent melt could cause S-wave velocity reduction of 5–8 per cent. On the other hand, a small volume of aqueous fluids may not produce detectable seismic wave anomalies as seismic data are not very sensitive to small amounts (<2 per cent) of water (Miller & Stewart 1990; Watanabe 1993; Hashim et al. 2013; Sinmyo & Keppler 2017). A study by Artemieva et al. (2004) concluded that the presence of partial melt and/or fluids in the uppermost mantle is required to explain the attenuation of seismic wave velocities in the continental upper mantle. All the above suggests that both partial melt and aqueous fluid may co-exist in the mantle zone characterized by low-resistivity and low-velocity anomalies. Thus, we conclude that the cause of decreased upper mantle resistivity below Bhuj is a combined effect of melt and aqueous fluid present in the mantle rock matrix. 4.3 Subvertical crustal conductive feature (C1) The near vertical modestly conductive feature C1, which originates from the top of the upper mantle conductive zone (C2) and cut through the crust under the Bhuj area, represents a channel for the upward migration of exsolved aqueous fluids from the deep/upper mantle fluid system. Therefore, the conductive feature C1 is the vertical fluid channel that brings fluids from the deep reservoir zone to the shallow crust levels. The near vertical conductive channel coincides closely with the KMF, which is the major fault along the rift axis at this part of the study area (Biswas 2005). A marked crustal (∼2–4 km) as well as lithosphere (∼10–20 km) thinning under this central Kutch rift zone, where most of the seismicity is concentrated, is noted by seismic modelling studies and inferred a conduit (extending from lower crust down to asthenospheric mantle) that facilitates the circulation of volatiles emanating from the carbonatite melts in the asthenosphere (Mandal 2019). The high resolution seismic tomographic study by Singh et al. (2019) revealed low Vp and Vs, and higher Vp/Vs below the KMF fault system at the 2001 Bhuj earthquake source (10–30 km) and at deeper depths into the mantle zone, which they attributed to the magma fluids in the rock matrix. The low resistivity and low velocity anomaly beneath the fault system endorse the deformed and weak nature of the fault. The coincident low velocity and low resistivity nature of rock matrix constituting the C1 anomaly unequivocally indicate fluids presence in the fault zone as the conductivity enhancement mechanism. Thus, the KMF appears to be a pathway through which fluids ascend from the upper mantle to the crust and get collected at favorable geological conditions/locations to form crustal fluid reservoirs (e.g. Kumar et al. 2017; Abdul Azeez et al. 2018; Singh et al. 2019). 4.4 Relation of fluids with seismicity Entrapped fluids pressure exert stress in the rock matrix, which increases as and when more fluids from the mantle penetrate into the brittle seismogenic part of the crust and get accumulated, thereby inducing earthquakes (e.g. Hubbert & Rubey 1959). Nevertheless, fluids alone cannot generate the required stress conditions to cause large (high to moderate) magnitude earthquakes. It is suggested that forces being generated at plate boundaries are transferred over long distances, therefore could cause/lead to stress accumulation at weak lithosphere locations in the interiors of the plate, such as intraplate rifts and faults (Gangopadhyay & Talwani 2003; Calignano et al. 2012). The weak nature (low strength) of the lithosphere underneath the Bhuj seismic zone, as implied by the low-resistivity of the mantle lithosphere due to interconnected fluid phases, is conducive for stress accumulation (Liu & Hasterok D. 2016). Such a stress generation in the Kutch rift zone is highly possible due to its close proximity to the (ongoing) India–Arabia–Eurasia Plate (collision) boundaries and therefore creates the background/primary stress conditions generally required for seismicity in intraplate regions (Stein et al. 2002), especially from the compressive stress regime following the India–Eurasia collision (Talwani 2017; Singh & Mandal 2018, Talwani 2014; Gahalaut et al. 2019). Fluids can act as the secondary stress generation mechanism through pore pressure buildup. Increased pore-fluid pressure adding to the pre-stressed faults facilitates to attain the critical stress conditions for rock failure and thus can trigger earthquakes (Garagash & Germanovich 2012). Persistent aftershocks in the area demand adequate and incessant fluid supply to sustain a fluid overpressure in the seismogenic crust. The upper mantle fluidized zone, which might be receiving fluids from the carbonatite partial melts in the asthenosphere (e.g. Mandal 2019), may be acting as a source for the continuous supply of fluids to maintain critical stress conditions inside the seismogenic part of the crust and thus could cause frequent seismicity. Thus, the fluids play a critical role in triggering large and moderate earthquakes in Bhuj together with the stresses resulted from regional plate-tectonic forces. 5 SUMMARY AND CONCLUSIONS The Kutch rift zone in the NW India is one of the most seismically active intraplate regions of the world as seen by the occurrence of large earthquakes for many centuries and the unusual persistent aftershock activity following the 26 January 2001 Bhuj earthquake of Mw = 7.7. Several of the geophysical studies inferred the presence of fluids in the crust of seismically active Bhuj area, but its deep origin is not fully understood. In this context, imaging of the lithosphere structure of the area was carried out using long-period magnetotelluric data (30–10 000 s) to understand the deep origin, nature and upward pathways of the fluids and contribute towards the efforts of global geoscientific community to gain more knowledge on the plausible generation mechanisms of intraplate seismicity in general and specifically for the Bhuj earthquake region. The 3-D resistivity model retrieved from the MT data exhibited two important low resistivity features, that is an upper mantle conductive zone C2 (∼50 Ωm to <100 Ωm) and a modestly conductive narrower sub-vertical conductive anomaly C1 (∼50–<150 Ωm) that originate from the top of the mantle conductive zone and extends upwards through the crust at a location coinciding with the surface trace of Kutch Mainland Fault (KMF) system. The MT model also showed resistive crustal domains (R1 and R2) on either side of C1 and typify a major part of the crustal section. Taking constraints from inputs available from other geophysical and geological data, the low resistivity of the lithospheric mantle can be attributed to the infiltration of fluids originated from carbonatite partial melts in the asthenosphere under the region. A detailed evaluation of the amount and nature of fluids indicated that a combination of small amounts of water and melts could produce the observed low resistivity of the mantle lithosphere beneath the Bhuj seismic zone. The moderately conductive near-vertical feature that appeared below the KMF is interpreted as the fluid channel carrying fluids from deeper levels of the lithosphere into the crustal level. This study gives evidence for the origin of fluids in the Bhuj region and fluids transport from the deep mantle into the intraplate crust. This study suggests a key role of fluids in intraplate seismicity of the Bhuj region through fluid pressure, which adds to the regional compressive stress regime caused by ongoing India–Eurasia collision and facilitate to attain the critical stress conditions for rock failure in the weak zones. The present study yields a possible subsurface geological scenario in the 2001 Bhuj intraplate earthquake epicentre zone using constraints from geology and other geophysical data (Fig. 11). Figure 11. Open in new tabDownload slide Summary of the subsurface geological interpretation of the lithospheric resistivity section obtained for the epicentre region of the 2001 Bhuj earthquake. Figure 11. Open in new tabDownload slide Summary of the subsurface geological interpretation of the lithospheric resistivity section obtained for the epicentre region of the 2001 Bhuj earthquake. SUPPORTING INFORMATION Figure S1. L-curve (Hansen 1992) constructed for the LMT profile. Note that roughness and RMS misfit error achieved after 200 iterations of each inversion with a particular tau value was utilized to construct the L-curve. The tau value of 3 (red solid circle) at the knee of the curve gives the smoothest resistivity model with lowest misfit error for the profile. Figure S2. Broad-band MT (BBMT) and long period MT (LMT) data measured at site L04. Data error is not shown. LMT XY apparent resistivity curve shows significant (a decade) down shift as compared to BBMT XY apparent resistivity curve. The YX components show a smooth continuation of apparent resistivity values from BBMT to LMT data range, which suggests a good match between BBMT and LMT measurements. The phase data shows smooth transition from BBMT to LMT range for both the components. The above observations indicate a significant static shift in LMT XY (TM mode in this study) apparent resistivity data. Accordingly, the LMT XY (TM) mode apparent resistivity is shifted upward (grey solid circles) to match the BBMT XY apparent resistivity data. Figure S3. Comparison between the observed and modelled 2-D MT and tipper responses at all the sites along the profile. Figure S4. Comparison of the observed and modelled 2-D MT and tipper data pseudo sections. Black dots represent data points used. Figure S5. Comparison between the observed data and responses of the final 3-D model at individual sites along the profile. Figure S6. Results of non-linear forward sensitivity test carried out for the resistive structure R2 of the 3-D model at the MT location C03. Figure S7. Estimated temperature–depth profile for the Bhuj seismic zone (modified from Pandey et al. 2017). Expected temperature at 50 and 80 km depths is marked. Please note: Oxford University Press is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the paper. ACKNOWLEDGEMENTS This study was supported by the Ministry of Earth Sciences (MoES), India, through the research funding sanctioned vide MoES/P.O.(Seismo)/1(107)/2010. Sincere thanks to V. M. Tiwari (Director, CSIR-NGRI) and M. Ravikumar (DG, ISR) for their kind permission to publish this work. Gary Egbert, Anna Kelbert and Naser Meqbel are acknowledged for providing their 3-D MT inversion code ModEM. Thanks to Naser Meqbel for providing 3DGRiD software. Critical questions and suggestions from Kerry Key and an anonymous reviewer helped to improve the manuscript. This manuscript is CSIR-NGRI contribution number NGRI/Lib/2019/Pub-92 under MLP-6404-28 (BPK) of CSIR-NGRI. Authors have no right to share the data used in this research paper. REFERENCES Abdul Azeez K.K. , 2016 . Magnetotelluric constraints on the occurrence of lower crustal earthquakes in the intra-plate setting of Central Indian Tectonic Zone , Acta Geol. Sin. 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TI - Lithospheric resistivity structure of the 2001 Bhuj earthquake aftershock zone
JF - Geophysical Journal International
DO - 10.1093/gji/ggaa556
DA - 2020-12-09
UR - https://www.deepdyve.com/lp/oxford-university-press/lithospheric-resistivity-structure-of-the-2001-bhuj-earthquake-LcIFSSvK0U
SP - 1980
EP - 2000
VL - 224
IS - 3
DP - DeepDyve
ER -