Petrophysical logs contribute in appraising productive sands of Lower Goru Formation, Kadanwari concession, Pakistan

Petrophysical logs contribute in appraising productive sands of Lower Goru Formation, Kadanwari... The interpretation of petrophysical logs unveil the reservoir traits and augment an intuition of hydrocarbon (gas) bearing zones. This study focused on interpretation of petrophysical signatures (encountered in Kadanwari-01, 03, 10 and 11) of Lower Goru Formation (LGF). LGF composed of shoreface sands and near shelf shale, deposited in Cretaceous age in mid- dle and lower Indus basins, Pakistan. The results upshot the reservoir potential tapped in interbeded sand packages of LGF. The petrophysical attributes such as shale content from radioactivity tools (GR, SGR), effective porosity from NPHI-RHOB response and average porosity, derived fluids saturation of porous sand reservoir pockets by averaging, the Wyllie–Rose permeability of the selected producing zones and matching of respective resistivity responses (LLD, LLS) quantified in LGF. Lithology indicator (M–N plots) and mineral identification (MID) plot provide a basis to classify the lithology of potential sands derived by neutron, density and sonic logs. The isoperimetric surfaces depict the spatial distribution of derived results of the corresponding prospect zone (PZ). A correlation from NE to SW of study area yields a lateral profile of physical characters and distribution of PZs. Prospect Zone-3 results exhibit good quality of reservoir sands (30–37 m thick), characterizing  from 0.12 to 0.23 and S 0.36–0.6. PZ-3 and PZ-4 are evaluated best prospect zones in this study ND hc and may be recommended for drilling. Keywords Petrophysical analysis · Reservoir evaluation · Lower Goru Formation · Kadanwari Introduction mature fields wherein conventional elements of hydrocar - bon trapping mechanisms are well established. The lower Pakistan’s discovered gas fields are speedily depleting Goru sands are producing reservoirs in Kadanwari gas field resources (Shar et al. 2017). The Kadanwari gas field (Fig.  1) on a regional scale. Certainly, many intervals of LGF are is located in gas prone Middle Indus Basin (MIB) of Paki- gas bearing, but lack sufficient permeability to produce gas stan. This gas field discovered in 1989 (Kadanwari-01, dis- at commercial profits (Ahmad and Chaudhry 2002; Ahmad covery well) and several successful discoveries from con- et al. 2007). ventional structural traps in early Cretaceous lower Goru This study primarily focuses on the petrophysical assess- sands convince the geoscientists for further exploration and ment of LGF up to 10’s of meter depth scale and presents development (Ahmad et al. 2004). Eleven wells have been detailed characterization of prospect zones. Literature drilled in this studied gas field (Ahmad and Chaudhry 2002). review and overview of seismic interpretations suggests Moreover, verbal communication with industry personal that two-dimensional seismic reflection profiles do not (ENI, Pakistan) reported 40 wells have been drilled in the efficiently map thin sand packages of faulted Kadanwari concession block. The literature review of MIB suggests that region. The petrophysical logs provide panaceas of such a significant amount of untapped potential can be unearthed cases and considered a handy tool (Khalid et al. 2015). The from structural and stratigraphic fairways of virgin plays in geophysical response provides remotely sensed geological conditions in boreholes and the interpretation of geophysical response add paramount reservoir estimations. The petro- * Muhammad Jahangir Khan physical exploration of thin sand packages of LGF help to mjahangir.bukc@bahria.edu.pk model one-dimensional geological signatures encountered Department of Earth and Environmental Sciences, Bahria in the understudy boreholes (Fig. 1) and when correlated University (Karachi Campus), Karachi, Pakistan Vol.:(0123456789) 1 3 1090 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Fig. 1 Site map of Kadanwari concession and understudy boreholes. Kadanwari-03 (K-03) similarly expressed Kadanwari-01 (K-01), and other boreholes with adjacent borehole the two-dimensional visualizations petroleum system of understudy area which is hypothesized provide lateral correlations. This study contributes to spa- on three tectonic episodes (Fig. 2). Upper brittle crust is tial mapping of newly identified gas prospects and present broken by the extensional forces under rifting phase-1 spatial distribution of evaluated reservoir attributes such as (middle Jurassic) into blocks during the seafloor spread- porosity distribution, permeability, thicknesses of zones of ing which was separated by the active faults. It appeared interest, shale content and distinguishes the hydrocarbon that during late Paleozoic to early Mesozoic stretching of fluid nature. However, the petrophysical examination of LGF initial rifted part stopped (represented by Hiatus in late is challenging in understudy field due to fluctuating deltaic Jurassic). The rifted crust remained as Indus basin failed conditions, mutable geological influences, varying miner - rift (Zaigham and Mallick 2000). Phase-2 (early Creta- alogical concentrations, sways of regional tectonic settings, ceous) represents the deposition of sediments on drifting structural geometries, shale washout in boreholes, and shale crust. Phase-3 (Late cretaceous) subsidence of the rifted instability in development phase etc. continental crust and at the same time deposition of the Mesozoic sediments in the Indus Basin. Later, up-lift and erosion signifies at the top of phase-3. The lithology stack An overview of geology and stratigraphy of MIB is depicted in Fig. 2 which highlights the basin fill sedimentary deposits. Geological evolution of the basins reveals the hypothesis of Sembar and Lower Goru shales are presumed source petroleum system, action of tectonic jargon and depositional of much of the gas fields in MIB. In Kadanwari area, disorders. Lower Goru sands form the reservoir and the transgres- Kadanwari gas field is one of the southernmost gas fields sive marine shales of lower and upper Goru formations of MIB which lies on the southeastern flank of the regional providing the top seal. Jacobabad High (Kazmi and Jan 1997). Early rifting of the The understudy field consists of a number of low relief Gondwanaland (Paleozoic) caused by rising basaltic magma fault and dip closures (Fig. 3). These wrench faults are par- (in upper Asthenosphere), squeezed the over-lying Litho- ticularly significant and divide the study area into faulted sphere (producing broad tectonic up-warp) which results in blocks (the graben of K-01 block bounded east and west by divergence and normal faulting in the upper lithosphere. The horsts K-3 and K-10 and K-11 blocks, respectively). A loss Lithosphere continued on thinning and resulted in magma of reservoir quality to the north provides a stratigraphic swelling and progression of seafloor spreading. trapping component. The trapping mechanism is a com- Literature review of authors (Ahmad and Chaudhry plex combination of structural dip, sealing faults and loss 2002; Dolan 1990; Kadri 1995; Kazmi and Jan 1997; of reservoir quality to the north. Munir et al. 2011) help us to develop the basin model and 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1091 Fig. 2 Generalized Stratigraphic Column of Middle Indus Basin (MIB). Modified after (Ahmad et al. 2004; Baig et al. 2016; Naeem et al. 2016) tool, respective log interval of targeted LGF encountered in understudy wells) is summarized in Table 1. Methodology The first assessment task is to know the subsurface lithol- ogy. GR log is more reliable for identification of lithology, moreover, double combo and triple combo cross-plots of neutroN–Density and neutroN–Density-sonic (M–N plots), respectively, used to reduce the uncertainty of interbeded shale and sandstone of LGF. Cross-plots of different rock properties define the visual representations of the corre- lation between them and provide virtual visualizations of quantum of data in comprehensive manner, which could be Fig. 3 Structural map of Kadanwari concession modified after further interpreted as the existence of hydrocarbons (oil/ (Ahmad and Chaudhry 2002) gas) or other fluids (water) and lithology. The resistivity logs in respective intervals highlight separation in resistiv- ity responses of LLD, LLS which signifies the substantial Data set hydrocarbon potential of the Lower Goru Sand Packages (LGSP). Standard Schlumberger charts certified interpreta- We have utilized digital geophysical responses of four boreholes (.las files) awarded by Directorate General of tion of lithology and hydrocarbons. Systematically progress- ing further, a detailed petrophysical analysis is executed to Petroleum Concession (DGPC), Pakistan. The petrophysi- cal logs express physical motif of stacked geological layers evaluate the reservoir faculties such as quantification of shale content (V ), effective porosity (  ), saturation of water as a function of depth. Key information of the data (such sh ND as type of log, measured physical property at respective (S ) and permeability (K). After considering environmental 1 3 1092 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Table 1 Metadata of petrophysical logs Geophysical Log Symbol Physical property Kadanwari-01 Kadanwari-03 Kadanwari-10 Kadanwari-11 depth range (m) depth range (m) depth range (m) depth range (m) Gamma Ray GR Radioactivity 1194–3952 1280–3486 2717–3502 2700–3540 Neutron Porosity NPHI Porosity 1194–3954 1280–3488 50–3549 2697–3540 Self-potential SP Natural Potential 7–3948 22–3485 2865–3522 2710–3543 Bulk Density RHOB Density 1194–3954 1280–3488 2865–3549 2697–3540 Sonic (Internal transit time) DT Compressional slowness 7–3948 22–3485 2865–3549 2710–3525 Micro-resistivity MSFL Mud cake resistivity 7–3948 22–3485 2865–3552 2710–3517 Shallow Resistivity LLS Invaded zone resistivity 1191–3948 22–3485 2865–3548 3089–3543 Deep resistivity LLD Uninvaded zone resistivity 1191–3948 22–3485 2865–3548 3045–3543 Photoelectric PEF Photoelectric effect 1194–3954 1280–3488 2865–3549 2725–3540 Thorium Log THOR Radioactivity 2922–3952 1280–3486 2717–3502 2700–3540 Potassium log POTA Radioactivity 1194–3954 1280–3486 2717–3502 2700–3540 correction, the GR index is computed by radioactivity tool and the double combo and triple combo cross-plots which avoid the over-estimation of reservoir porosity of (Fig. 4b, c) of neutroN–Density and neutroN–Density- LGSP. The effective porosity is computed from neutron sonic (M–N plots), respectively, confirms the reservoir porosity and bulk density logs and later, average effec- lithology as “sandstone” of LGSP. The sandstone pack- tive porosity was computed by the combination of derived ages acting as reservoir within understudy area has been porosities. In the absence of core data, the used empirical identified through low values of GR, neutroN–Density methods are reliable to predict the effective reservoir poros- (ND) cross plot in which the accumulation of clusters ity. Derived saturation (water/hydrocarbon) of porous reser- at the base of standard sandstone axis (green color, voir of LGSP as a function of R has been calculated by SP Fig. 4b), similarly M–N cross-plots show the clusters log. The permeability (K) of the reservoir is calculated for falling dominantly in Quartz region. This work classi- precise estimation of the saturation of gas. The information fies four targeted prospect zones in Kadanwari Block about dominant matrix of LGSP and trapped hydrocarbon and unearths their hydrocarbon potential. The prospect type is inferred from MID plots. The isoparametric maps of zones are chronologically ranked as PZ-1 to PZ-4. key findings showcase the interpolated distribution of shale b. Reservoir assessment content, effective porosity, saturation of hydrocarbons, and The credibility of sand reservoir is evaluated through net pay thickness of reservoir of the paramount prospects. estimations of petrophysical parameters such as V , , sh ND S and K. The numerical estimates of all proposed pros- pect zones referred in Table 2. The maps of prospect Results and discussion zones yield lateral variation of petrophysical traits. The isoperimetric maps of porosity (total and effective), The comprehensive presentation upshots semi-quantitative water and hydrocarbon saturations, shale volume, gross and qualitative interpretation of petrophysical logs made thickness are prepared to evaluate the spatial hydrocar- with an aim to evaluate petrophysical faculties of targeted bons potential in the study area. However, the spatial LGSP as reservoir of the proposed prospect zones. distribution of regional prospects is depicted in Fig. 5. a. Lithology Interpretation The interpretation of lithology of targeted zones i. Volume of Shale (V ) sh derived from integration of log responses and cross- Volume of shale is a significant indicator of reservoir plots. GR index is primarily a function of shale content quality. In petrophysical assessment, the low values of because the GR tool is sensitive to detect radioactive shale content depicting the cleanliness of the sandstone emission dominantly concentrated in clay mineral of (Hussain et al. 2017). In case of sandstone the low GR shale and clean sand (feldspar rich). However, GR log value usually considered a good reservoir and vice readings increase as the proportion of shale increases in versa. Shale content has been calculated by notion: the formations. The GR response drops in front sand- GR log − GRmin stones, track-1 (each understudy wells, Fig. 4a) high- V = Gamma Ray Index = . sh GR max − GRmin lights targeted zones (illustrated by four different colors) (1) 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1093 Fig. 4 a Correlation of petro- physical curves in understudy wells (AA’ from SW–NE). b Standard cross-plots (Neutron porosity on X-axis and bulk density on Y-axis). Gray—Pros- pect Zone-1, Blue—Prospect Zone-2, Yellow—Prospect Zone-3, and Purple—Prospect Zone-4. c Mineral assem- blages illustrate the standard M–N cross plot in respective boreholes. Gray—Prospect Zone-1, Blue—Prospect Zone-2, Yellow—Prospect Zone-3, and Purple—Prospect Zone-4. d Mineral identifica- tion plots (MID), under study wells. Gray—Prospect Zone-1, Blue—Prospect Zone-2, Yel- low—Prospect Zone-3, and Purple—Prospect Zone-4 1 3 1094 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Fig. 4 (continued) 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1095 Table 2 Petrophysical evaluation of prospect zones Boreholes name Lat degree Log degree Depth meter Thick- V (%) PHI avg (%) S avg (%) S (%) Perme- sh w hc ness ability meter millidarcy PZ -1 Kadanwari-03 27.156861 69.1975 3270 3278 8 0.629 0.201 0.33 0.66 1983.45 Kadanwari-01 27.148056 69.226667 3272 3282 10 0.47 0.17 0.71 0.28 1595.15 Kadanwari-10 27.172705 69.236612 3279 3290 11 0.43 0.16 0.69 0.31 1212.02 Kadanwari-11 27.1835 69.238539 3292 3305 13 0.5 0.22 0.50 0.50 1555.09 PZ-2 Kadanwari-03 27.156861 69.1975 3316 3334 18 0.51 0.199 0.22 0.77 1931.3 Kadanwari-01 27.148056 69.226667 3320 3340 20 0.497 0.229 0.458 0.541 4446.16 Kadanwari-10 27.172705 69.236612 3325 3346 21 0.711 0.166 0.684 0.315 780.92 Kadanwari-11 27.1835 69.238539 3338 3359 21 0.54 0.214 0.559 0.44 2174.12 PZ -3 Kadanwari-03 27.156861 69.1975 3344 3381 37 0.63 0.148 0.39 0.609 750.26 Kadanwari-01 27.148056 69.226667 3350 3380 30 0.62 0.23 0.414 0.58 5695 Kadanwari-10 27.172705 69.236612 3358 3392 34 0.77 0.16 0.39 0.6 1192.68 Kadanwari-11 27.1835 69.238539 3370 3403 33 0.637 0.12 0.63 0.369 409.68 PZ -4 Kadanwari-03 27.156861 69.1975 - - - - - - - - Kadanwari-01 27.148056 69.226667 3504 3555 51 0.28 0.406 0.158 0.841 35475.86 Kadanwari-10 27.172705 69.236612 3514 3537 23 0.61 0.109 0.512 0.487 3525.46 Kadanwari-11 27.1835 69.238539 3525 3541 16 0.53 0.22 0.56 0.44 2047.12 V has been calculated and average values of each The combination of neutron porosity (  ) and sh N prospect zone given in Table 2. The maps of derived density porosity (  ) is denoted by  . Neutr on D T ND shale content distribution (Fig. 5A, A’) of reservoir zones log provides the direct porosity (  ) of the reservoir, of prospect zone 2 (PZ-2) and prospect zone 3 (PZ-3), however, the density porosity (  ) is computed by respectively. PZ-2 has shale content estimated 49.7% at the following equation: PHID = (RHOB − RLST)/ Kadanwari-01 (southwest of study area), whereas maxi- (RHOMF − RLST), where RHOMF is the mud filtrate mum 71% at Kadanwari-10 (northeast). High values of density equal by default to 1 g/cc if no input given as V in the reservoir zone are influenced by clay minerals bulk density fluid, RLST is the limestone grain den - sh (Fig. 4d) which attempt to reduce the effective porosity. sity by default set to 2.71 g/cc, and RHOB is the bulk The interpolation suggests that the PZ-2 has more clean- density. liness of reservoir in southwest of Kadanwari than north- The derived average value of  in the targeted ND east. PZ-3 has varying V from 62% (Kadanwari-01, zone is given in Table 2. The distribution maps of sh E southwest of study area) to77% for Kadanwari-10. The for PZ-2 are shown in Fig.  5b; the effective poros- interpolation trend indicates a similar character of V ity is estimated within range of 16% (Kadanaweri-10) sh estimated for both regional prospects. to 22.9% (Kadanwari-01).The maximum value of ii. Effective porosity effective porosity originates from northeast of study Reservoir quality is a function of effective porosity. area while the lowermost value of effective poros- The high values of effective porosities refer to better ity in adjacent well Kadanwari-10, influenced by the volume estimates and thus theoretically a good reser- structure; further moving southwest of the study area voir and vice versa. the effective porosity increased and estimated high- The effective porosity of zone of interest has been est. PZ-3 characterizes with  12% (Kadanwari-11) computed from neutron porosity and bulk density to 23% (Kadanwari-01); the variograph surface logs. The average values of effective porosities derived (Fig.  5B’) depicts that the effective porosity of the from dual logs was computed. In the absence of core respective zone increases southwest of the study area. data, the empirical methods are reliable to predict the iii. Saturation of water effective reservoir porosity(Asquith et al. 2004).The Indonesian equation (Poupon and Leveaux 1971) is effective porosity has been calculated by notion: one of the effective porosity saturation methods which is applied to calculate S of targeted LGSP; the used Effective porosity =  =  −  × V . equation provides comparatively easy computation E T T sh ND SH (2) and shows numerically positive results (greater than 1 3 1096 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Prospect Zone 2Prospect Zone 3 A´ BB´ CC´ DD´ Fig. 5 Left panel shows the prospect zones 2 and right panel shows prospect zone 3.a Volume of shale, b average effective porosity, c saturation of Hydrocarbons, d thickness 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1097 zero). Other quadratic and iterative solution models certainly the gas accumulations of four targeted pros- can calculate negative S which is uncertain. Where pects. the petrophysical traits are the effective porosity, °ϕ , Hydrocarbon bearing zone characterized with high volume and resistivity log reading of 100% shale resistivity values, porosity high, permeability high, (ohm. m) (V and R ) and water resistivity (R ), saturation of water low, and less V suggest clean sh sh w sh deep resistivity log gives true resistivity (R ) at 100% sand. water saturation (ohm. m), cementation factor (m) and v. Permeability (K) saturation exponent (n). The computed results exhibit Permeability estimates provide the unbounded fluid better understanding of shaly sand reservoir (Fig. 4d), flow in porous reservoir, Wyllie–Rose permeability of the selected LGSP was estimated by the following −1 equation: ⎧ ⎡ ⎤⎫ ⎛ m ⎞ � � ⎪ ⎢ ⎥⎪ 2−V sh ⎜ ⎟ V e ⎪ ⎢ ⎥⎪ sh ⎜ ⎟ (3) S = R + . ⎨ ⎢ ⎥⎬ w t K = K . R ⎜ R ⎟ w Sh w ⎪ ⎢ ⎥⎪ S ⎜ ⎟ ⎪ ⎢ ⎥⎪ ⎝ ⎠ ⎩ ⎣ ⎦⎭ We have adopted Morris–Biggs estimates with con- stants d = 6.0, e = 2 and K  = 6500 for gas. The saturation of water within the consolidated Typically, porosity has to exceed 18% and permea- sandstone estimated with the following parameters: bility to be greater than 2 milliDarcy for a sand to pro- tortuosity factor (a = 0.81), cementation exponent duce gas at commercial rates in Kadanwari (Ahmad (m = 2) and saturation exponent (n = 2) (Asquith et al. and Chaudhry 2002). The permeability findings for 2004). Hydrocarbon saturation (S ) is a function of PZ-2 suggest that permeability ranges from ~ 0.7 hc Sw. PZ-2 has S minimum 22% (Kadanweri-03) and Darcy to ~ 4.4 Darcy, whereas for PZ-3 ~ 0.4 Darcy to conversely S 77% which is maximum (southwest of ~ 5.6 Darcy. Quadri and Quadri (1996) suggested the hc study area). Although S for PZ-2 is not lesser than estimation of permeability for lower Goru may exceed hc 31.5%. The interpolated S demonstrates (Fig.  5c) 1 Darcy. hc that hydrocarbon (gas saturation) spatially varies east– west and relatively increases towards southwest of the study area. PZ-3 is characterized with minimum S c. Finally, the thickness distribution maps of PZ-2 (Fig. 5d) hc 36.9% (Kadanwari-11) to 60.9% (Kadanwari-03), and suggest that thickness of gas prone reservoir of LGSP spatially, S increases towards southwestern side of increases in northeast of the study area. The interpolated hc the study area. thickness for PZ-3 (Fig. 5D’) increases southeast of the iv. Hydrocarbon identification study area which ranges with relatively thick packages Furthermore, the delineation of the reservoir zones from 30 to 37 m. has been made through N–D crossover (track-2 of d. The mineral identification (MID) plots are machinated each well, Fig. 4a) and resistivity log analyses (track-3 between photoelectric effect (PEF) and thorium–potas- of each well, Fig.  4a) and the Schlumberger cross- sium ratio (TPRA) which provide ample clue that the plots (Fig.  4b, c). In some conditions, it is claimed reservoir has little dirtiness, encountered in each that there’s a shale rock formation according to high reading for gamma ray, density log and neutron log, but resistivity logs increase; during this circumstance, Conclusion and recommendations the sharp increase in resistivity logs is due to a dia- genetic process such as compaction or cementation The petrophysical studies unearth hydrocarbon potential of and there’s no water content during this condition as four prospect zones (PZ-1 to PZ-4) in Cretaceous age LGF a result of water bearings decrease the resistivity. The which is a productive Kadanwari field. GR index, double separations of resistivity logs (LLD, LLS, MSFL) combo and triple combo plots ascertain sandstone lithology. suggest the presence of hydrocarbon but discrimina- The cross-plots, resistivity separation, and N–D crossover tion between fluid type (oil and gas) at this stage is discriminate gas accumulation. The petrophysical assess- still quizzing. In pursuance, we have utilized N–D ment of reservoir concluded that shallower PZ-1 (11  m plot (Fig. 4b) and M–N plot (Fig. 4c) todiscriminate average thickness) and deepest PZ-4 (30 m avg. thickness), the hydrocarbon type. The rising clusters (reservoir although the intermediate depth zone PZ-2 (18–21 m thick) interval) ascertain least density reservoir pore fluid, and PZ-3 (30–37 m thick) are main prospects of this study. PZ-2 and PZ-3 hold key indicators: low GR, crossover of 1 3 1098 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Lower and Middle Indus Platform, Pakistan: In: PAPG, Annual density porosity, separation of resistivities, low S , high Technical Conference, p. 85–104 hydrocarbon saturation and favorable permeability. PZ-2 Ahmad N, Spadini G, Palekar A, Subhani MA (2007) Porosity predic- results highlight reservoir sands characterizing V from sh tion using 3D seismic inversion Kadanwari Gas Field, Pakistan. 0.49 to 0.71,  from 0.16 to 0.22, S from 0.22 to 0.68 Pak J Hydrocarb Res 17:95–102 ND w Asquith GB, Krygowski D, Gibson CR (2004) Basic well log analysis, and S 0.31–0.77. PZ-3 results exhibit good quality of res- hc American Association of Petroleum Geologists, Tulsa ervoir sands having more thickness and characterizing V sh Baig MO, Harris N, Ahmed H, Baig M (2016) Controls on reservoir 0.62–0.77,  from 0.12 to 0.23, S from 0.39 to 0.63 and ND w diagenesis in the Lower Goru Sandstone Formation, Lower Indus S 0.36–0.6. Thus, PZ-3 is thick package of sand and shows basin, Pakistan. J Pet Geol 39(1):29–47 hc Dolan P (1990) Pakistan: a history of petroleum exploration and future comparatively better reservoir characteristics. The quanti- potential. Geological Society, London, 50, pp 503–524 fication of petrophysical analysis reveals that the prospect Hussain M, Ahmed N, Chun WY, Khalid P, Mahmood A, Ahmad SR, zones Lower Goru Formation have good potential and sig- Rasool U (2017) Reservoir characterization of basal sand zone nificant accumulation of hydrocarbons and this study will of lower Goru Formation by petrophysical studies of geophysical logs. J Geol Soc India 89(3):331–338 enhance future hydrocarbon exploration and exploitation Kadri IB (1995) Petroleum geology of Pakistan, Pakistan Petroleum activities in parts of lower Indus basin of Pakistan. However, Limited, Karachi results are acquired only based on petrophysical analysis. To Kazmi AH, Jan MQ (1997), Geology and tectonics of Pakistan. strengthen the estimated results, we recommend geochemis- Graphic publishers, Santa Ana Khalid P, Yasin Q, Sohail G, Kashif JM (2015) Integrating core and try data for source rock basic information, core for absolute wireline log data to evaluate porosity of Jurassic formations of reservoir properties, and 3D seismic reflection datasets for Injra-1 and Nuryal-2 wells, Western Potwar, Pakistan. J Geol Soc the development of local play concepts and prospect/lead India 86(5):553 assessments. Based on good quality reservoir characteristics Munir K, Iqbal MA, Farid A, Shabih SM (2011) Mapping the produc- tive sands of Lower Goru Formation by using seismic stratigraphy of PZ-4 (Table 2 and Fig. 4a), it is also recommended to drill and rock physical studies in Sawan area, southern Pakistan: a case all the wells down to this zone in the concession blocks and study. J Pet Explor Prod Technol 1(1):33–42 may invest on this productive zone in the future. Naeem M, Jafri MK, Moustafa SS, AL-Arifi NS, Asim S, Khan F, Ahmed N (2016) Seismic and well log driven structural and petro- Acknowledgements We thank the potential reviewers for their sugges- physical analysis of the Lower Goru Formation in the Lower Indus tions to improve the manuscript. We also thank DGPC for providing Basin, Pakistan. Geosci J 20(1):57–75 necessary data, and acknowledge the moral support of PPL Chair in Poupon A, Leveaux J (1971) Evaluation of water saturation in shaly facilitation of this study in Digital Geophysical Data Lab at Bahria formations. In: Proceedings SPWLA 12th Annual Logging Sym- University Karachi Campus. posium, Society of Petrophysicists and Well-Log Analysts Quadri V-u-N, Quadri S (1996) Anatomy of success in oil and gas exploration in Pakistan, 1915–94. Oil Gas J 94:20 Open Access This article is distributed under the terms of the Crea- Shar AM, Mahesar AA, Memon KR (2017) Could shale gas meet tive Commons Attribution 4.0 International License (http://creat iveco energy deficit: its current status and future prospects. J Pet Explor mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- Prod Technol. https ://doi.org/10.1007/s1320 2-017-0399-y tion, and reproduction in any medium, provided you give appropriate Zaigham NA, Mallick KA (2000) Prospect of hydrocarbon associated credit to the original author(s) and the source, provide a link to the with fossil-rift structures of the southern Indus basin, Pakistan: Creative Commons license, and indicate if changes were made. AAPG Bull, 84(11):1833–1848 Publisher’s Note Springer Nature remains neutral with regard to References jurisdictional claims in published maps and institutional affiliations. Ahmad N, Chaudhry S (2002) Kadanwari gas field, Pakistan: a disap- pointment turns into an attractive development opportunity. Petrol Geosci 8(4):307–316 Ahmad N, Fink P, Sturrock S, Mahmood T, Ibrahim M (2004) Sequence stratigraphy as predictive tool in Lower Goru Fairway, 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Petroleum Exploration and Production Technology Springer Journals

Petrophysical logs contribute in appraising productive sands of Lower Goru Formation, Kadanwari concession, Pakistan

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Abstract

The interpretation of petrophysical logs unveil the reservoir traits and augment an intuition of hydrocarbon (gas) bearing zones. This study focused on interpretation of petrophysical signatures (encountered in Kadanwari-01, 03, 10 and 11) of Lower Goru Formation (LGF). LGF composed of shoreface sands and near shelf shale, deposited in Cretaceous age in mid- dle and lower Indus basins, Pakistan. The results upshot the reservoir potential tapped in interbeded sand packages of LGF. The petrophysical attributes such as shale content from radioactivity tools (GR, SGR), effective porosity from NPHI-RHOB response and average porosity, derived fluids saturation of porous sand reservoir pockets by averaging, the Wyllie–Rose permeability of the selected producing zones and matching of respective resistivity responses (LLD, LLS) quantified in LGF. Lithology indicator (M–N plots) and mineral identification (MID) plot provide a basis to classify the lithology of potential sands derived by neutron, density and sonic logs. The isoperimetric surfaces depict the spatial distribution of derived results of the corresponding prospect zone (PZ). A correlation from NE to SW of study area yields a lateral profile of physical characters and distribution of PZs. Prospect Zone-3 results exhibit good quality of reservoir sands (30–37 m thick), characterizing  from 0.12 to 0.23 and S 0.36–0.6. PZ-3 and PZ-4 are evaluated best prospect zones in this study ND hc and may be recommended for drilling. Keywords Petrophysical analysis · Reservoir evaluation · Lower Goru Formation · Kadanwari Introduction mature fields wherein conventional elements of hydrocar - bon trapping mechanisms are well established. The lower Pakistan’s discovered gas fields are speedily depleting Goru sands are producing reservoirs in Kadanwari gas field resources (Shar et al. 2017). The Kadanwari gas field (Fig.  1) on a regional scale. Certainly, many intervals of LGF are is located in gas prone Middle Indus Basin (MIB) of Paki- gas bearing, but lack sufficient permeability to produce gas stan. This gas field discovered in 1989 (Kadanwari-01, dis- at commercial profits (Ahmad and Chaudhry 2002; Ahmad covery well) and several successful discoveries from con- et al. 2007). ventional structural traps in early Cretaceous lower Goru This study primarily focuses on the petrophysical assess- sands convince the geoscientists for further exploration and ment of LGF up to 10’s of meter depth scale and presents development (Ahmad et al. 2004). Eleven wells have been detailed characterization of prospect zones. Literature drilled in this studied gas field (Ahmad and Chaudhry 2002). review and overview of seismic interpretations suggests Moreover, verbal communication with industry personal that two-dimensional seismic reflection profiles do not (ENI, Pakistan) reported 40 wells have been drilled in the efficiently map thin sand packages of faulted Kadanwari concession block. The literature review of MIB suggests that region. The petrophysical logs provide panaceas of such a significant amount of untapped potential can be unearthed cases and considered a handy tool (Khalid et al. 2015). The from structural and stratigraphic fairways of virgin plays in geophysical response provides remotely sensed geological conditions in boreholes and the interpretation of geophysical response add paramount reservoir estimations. The petro- * Muhammad Jahangir Khan physical exploration of thin sand packages of LGF help to mjahangir.bukc@bahria.edu.pk model one-dimensional geological signatures encountered Department of Earth and Environmental Sciences, Bahria in the understudy boreholes (Fig. 1) and when correlated University (Karachi Campus), Karachi, Pakistan Vol.:(0123456789) 1 3 1090 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Fig. 1 Site map of Kadanwari concession and understudy boreholes. Kadanwari-03 (K-03) similarly expressed Kadanwari-01 (K-01), and other boreholes with adjacent borehole the two-dimensional visualizations petroleum system of understudy area which is hypothesized provide lateral correlations. This study contributes to spa- on three tectonic episodes (Fig. 2). Upper brittle crust is tial mapping of newly identified gas prospects and present broken by the extensional forces under rifting phase-1 spatial distribution of evaluated reservoir attributes such as (middle Jurassic) into blocks during the seafloor spread- porosity distribution, permeability, thicknesses of zones of ing which was separated by the active faults. It appeared interest, shale content and distinguishes the hydrocarbon that during late Paleozoic to early Mesozoic stretching of fluid nature. However, the petrophysical examination of LGF initial rifted part stopped (represented by Hiatus in late is challenging in understudy field due to fluctuating deltaic Jurassic). The rifted crust remained as Indus basin failed conditions, mutable geological influences, varying miner - rift (Zaigham and Mallick 2000). Phase-2 (early Creta- alogical concentrations, sways of regional tectonic settings, ceous) represents the deposition of sediments on drifting structural geometries, shale washout in boreholes, and shale crust. Phase-3 (Late cretaceous) subsidence of the rifted instability in development phase etc. continental crust and at the same time deposition of the Mesozoic sediments in the Indus Basin. Later, up-lift and erosion signifies at the top of phase-3. The lithology stack An overview of geology and stratigraphy of MIB is depicted in Fig. 2 which highlights the basin fill sedimentary deposits. Geological evolution of the basins reveals the hypothesis of Sembar and Lower Goru shales are presumed source petroleum system, action of tectonic jargon and depositional of much of the gas fields in MIB. In Kadanwari area, disorders. Lower Goru sands form the reservoir and the transgres- Kadanwari gas field is one of the southernmost gas fields sive marine shales of lower and upper Goru formations of MIB which lies on the southeastern flank of the regional providing the top seal. Jacobabad High (Kazmi and Jan 1997). Early rifting of the The understudy field consists of a number of low relief Gondwanaland (Paleozoic) caused by rising basaltic magma fault and dip closures (Fig. 3). These wrench faults are par- (in upper Asthenosphere), squeezed the over-lying Litho- ticularly significant and divide the study area into faulted sphere (producing broad tectonic up-warp) which results in blocks (the graben of K-01 block bounded east and west by divergence and normal faulting in the upper lithosphere. The horsts K-3 and K-10 and K-11 blocks, respectively). A loss Lithosphere continued on thinning and resulted in magma of reservoir quality to the north provides a stratigraphic swelling and progression of seafloor spreading. trapping component. The trapping mechanism is a com- Literature review of authors (Ahmad and Chaudhry plex combination of structural dip, sealing faults and loss 2002; Dolan 1990; Kadri 1995; Kazmi and Jan 1997; of reservoir quality to the north. Munir et al. 2011) help us to develop the basin model and 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1091 Fig. 2 Generalized Stratigraphic Column of Middle Indus Basin (MIB). Modified after (Ahmad et al. 2004; Baig et al. 2016; Naeem et al. 2016) tool, respective log interval of targeted LGF encountered in understudy wells) is summarized in Table 1. Methodology The first assessment task is to know the subsurface lithol- ogy. GR log is more reliable for identification of lithology, moreover, double combo and triple combo cross-plots of neutroN–Density and neutroN–Density-sonic (M–N plots), respectively, used to reduce the uncertainty of interbeded shale and sandstone of LGF. Cross-plots of different rock properties define the visual representations of the corre- lation between them and provide virtual visualizations of quantum of data in comprehensive manner, which could be Fig. 3 Structural map of Kadanwari concession modified after further interpreted as the existence of hydrocarbons (oil/ (Ahmad and Chaudhry 2002) gas) or other fluids (water) and lithology. The resistivity logs in respective intervals highlight separation in resistiv- ity responses of LLD, LLS which signifies the substantial Data set hydrocarbon potential of the Lower Goru Sand Packages (LGSP). Standard Schlumberger charts certified interpreta- We have utilized digital geophysical responses of four boreholes (.las files) awarded by Directorate General of tion of lithology and hydrocarbons. Systematically progress- ing further, a detailed petrophysical analysis is executed to Petroleum Concession (DGPC), Pakistan. The petrophysi- cal logs express physical motif of stacked geological layers evaluate the reservoir faculties such as quantification of shale content (V ), effective porosity (  ), saturation of water as a function of depth. Key information of the data (such sh ND as type of log, measured physical property at respective (S ) and permeability (K). After considering environmental 1 3 1092 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Table 1 Metadata of petrophysical logs Geophysical Log Symbol Physical property Kadanwari-01 Kadanwari-03 Kadanwari-10 Kadanwari-11 depth range (m) depth range (m) depth range (m) depth range (m) Gamma Ray GR Radioactivity 1194–3952 1280–3486 2717–3502 2700–3540 Neutron Porosity NPHI Porosity 1194–3954 1280–3488 50–3549 2697–3540 Self-potential SP Natural Potential 7–3948 22–3485 2865–3522 2710–3543 Bulk Density RHOB Density 1194–3954 1280–3488 2865–3549 2697–3540 Sonic (Internal transit time) DT Compressional slowness 7–3948 22–3485 2865–3549 2710–3525 Micro-resistivity MSFL Mud cake resistivity 7–3948 22–3485 2865–3552 2710–3517 Shallow Resistivity LLS Invaded zone resistivity 1191–3948 22–3485 2865–3548 3089–3543 Deep resistivity LLD Uninvaded zone resistivity 1191–3948 22–3485 2865–3548 3045–3543 Photoelectric PEF Photoelectric effect 1194–3954 1280–3488 2865–3549 2725–3540 Thorium Log THOR Radioactivity 2922–3952 1280–3486 2717–3502 2700–3540 Potassium log POTA Radioactivity 1194–3954 1280–3486 2717–3502 2700–3540 correction, the GR index is computed by radioactivity tool and the double combo and triple combo cross-plots which avoid the over-estimation of reservoir porosity of (Fig. 4b, c) of neutroN–Density and neutroN–Density- LGSP. The effective porosity is computed from neutron sonic (M–N plots), respectively, confirms the reservoir porosity and bulk density logs and later, average effec- lithology as “sandstone” of LGSP. The sandstone pack- tive porosity was computed by the combination of derived ages acting as reservoir within understudy area has been porosities. In the absence of core data, the used empirical identified through low values of GR, neutroN–Density methods are reliable to predict the effective reservoir poros- (ND) cross plot in which the accumulation of clusters ity. Derived saturation (water/hydrocarbon) of porous reser- at the base of standard sandstone axis (green color, voir of LGSP as a function of R has been calculated by SP Fig. 4b), similarly M–N cross-plots show the clusters log. The permeability (K) of the reservoir is calculated for falling dominantly in Quartz region. This work classi- precise estimation of the saturation of gas. The information fies four targeted prospect zones in Kadanwari Block about dominant matrix of LGSP and trapped hydrocarbon and unearths their hydrocarbon potential. The prospect type is inferred from MID plots. The isoparametric maps of zones are chronologically ranked as PZ-1 to PZ-4. key findings showcase the interpolated distribution of shale b. Reservoir assessment content, effective porosity, saturation of hydrocarbons, and The credibility of sand reservoir is evaluated through net pay thickness of reservoir of the paramount prospects. estimations of petrophysical parameters such as V , , sh ND S and K. The numerical estimates of all proposed pros- pect zones referred in Table 2. The maps of prospect Results and discussion zones yield lateral variation of petrophysical traits. The isoperimetric maps of porosity (total and effective), The comprehensive presentation upshots semi-quantitative water and hydrocarbon saturations, shale volume, gross and qualitative interpretation of petrophysical logs made thickness are prepared to evaluate the spatial hydrocar- with an aim to evaluate petrophysical faculties of targeted bons potential in the study area. However, the spatial LGSP as reservoir of the proposed prospect zones. distribution of regional prospects is depicted in Fig. 5. a. Lithology Interpretation The interpretation of lithology of targeted zones i. Volume of Shale (V ) sh derived from integration of log responses and cross- Volume of shale is a significant indicator of reservoir plots. GR index is primarily a function of shale content quality. In petrophysical assessment, the low values of because the GR tool is sensitive to detect radioactive shale content depicting the cleanliness of the sandstone emission dominantly concentrated in clay mineral of (Hussain et al. 2017). In case of sandstone the low GR shale and clean sand (feldspar rich). However, GR log value usually considered a good reservoir and vice readings increase as the proportion of shale increases in versa. Shale content has been calculated by notion: the formations. The GR response drops in front sand- GR log − GRmin stones, track-1 (each understudy wells, Fig. 4a) high- V = Gamma Ray Index = . sh GR max − GRmin lights targeted zones (illustrated by four different colors) (1) 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1093 Fig. 4 a Correlation of petro- physical curves in understudy wells (AA’ from SW–NE). b Standard cross-plots (Neutron porosity on X-axis and bulk density on Y-axis). Gray—Pros- pect Zone-1, Blue—Prospect Zone-2, Yellow—Prospect Zone-3, and Purple—Prospect Zone-4. c Mineral assem- blages illustrate the standard M–N cross plot in respective boreholes. Gray—Prospect Zone-1, Blue—Prospect Zone-2, Yellow—Prospect Zone-3, and Purple—Prospect Zone-4. d Mineral identifica- tion plots (MID), under study wells. Gray—Prospect Zone-1, Blue—Prospect Zone-2, Yel- low—Prospect Zone-3, and Purple—Prospect Zone-4 1 3 1094 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Fig. 4 (continued) 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1095 Table 2 Petrophysical evaluation of prospect zones Boreholes name Lat degree Log degree Depth meter Thick- V (%) PHI avg (%) S avg (%) S (%) Perme- sh w hc ness ability meter millidarcy PZ -1 Kadanwari-03 27.156861 69.1975 3270 3278 8 0.629 0.201 0.33 0.66 1983.45 Kadanwari-01 27.148056 69.226667 3272 3282 10 0.47 0.17 0.71 0.28 1595.15 Kadanwari-10 27.172705 69.236612 3279 3290 11 0.43 0.16 0.69 0.31 1212.02 Kadanwari-11 27.1835 69.238539 3292 3305 13 0.5 0.22 0.50 0.50 1555.09 PZ-2 Kadanwari-03 27.156861 69.1975 3316 3334 18 0.51 0.199 0.22 0.77 1931.3 Kadanwari-01 27.148056 69.226667 3320 3340 20 0.497 0.229 0.458 0.541 4446.16 Kadanwari-10 27.172705 69.236612 3325 3346 21 0.711 0.166 0.684 0.315 780.92 Kadanwari-11 27.1835 69.238539 3338 3359 21 0.54 0.214 0.559 0.44 2174.12 PZ -3 Kadanwari-03 27.156861 69.1975 3344 3381 37 0.63 0.148 0.39 0.609 750.26 Kadanwari-01 27.148056 69.226667 3350 3380 30 0.62 0.23 0.414 0.58 5695 Kadanwari-10 27.172705 69.236612 3358 3392 34 0.77 0.16 0.39 0.6 1192.68 Kadanwari-11 27.1835 69.238539 3370 3403 33 0.637 0.12 0.63 0.369 409.68 PZ -4 Kadanwari-03 27.156861 69.1975 - - - - - - - - Kadanwari-01 27.148056 69.226667 3504 3555 51 0.28 0.406 0.158 0.841 35475.86 Kadanwari-10 27.172705 69.236612 3514 3537 23 0.61 0.109 0.512 0.487 3525.46 Kadanwari-11 27.1835 69.238539 3525 3541 16 0.53 0.22 0.56 0.44 2047.12 V has been calculated and average values of each The combination of neutron porosity (  ) and sh N prospect zone given in Table 2. The maps of derived density porosity (  ) is denoted by  . Neutr on D T ND shale content distribution (Fig. 5A, A’) of reservoir zones log provides the direct porosity (  ) of the reservoir, of prospect zone 2 (PZ-2) and prospect zone 3 (PZ-3), however, the density porosity (  ) is computed by respectively. PZ-2 has shale content estimated 49.7% at the following equation: PHID = (RHOB − RLST)/ Kadanwari-01 (southwest of study area), whereas maxi- (RHOMF − RLST), where RHOMF is the mud filtrate mum 71% at Kadanwari-10 (northeast). High values of density equal by default to 1 g/cc if no input given as V in the reservoir zone are influenced by clay minerals bulk density fluid, RLST is the limestone grain den - sh (Fig. 4d) which attempt to reduce the effective porosity. sity by default set to 2.71 g/cc, and RHOB is the bulk The interpolation suggests that the PZ-2 has more clean- density. liness of reservoir in southwest of Kadanwari than north- The derived average value of  in the targeted ND east. PZ-3 has varying V from 62% (Kadanwari-01, zone is given in Table 2. The distribution maps of sh E southwest of study area) to77% for Kadanwari-10. The for PZ-2 are shown in Fig.  5b; the effective poros- interpolation trend indicates a similar character of V ity is estimated within range of 16% (Kadanaweri-10) sh estimated for both regional prospects. to 22.9% (Kadanwari-01).The maximum value of ii. Effective porosity effective porosity originates from northeast of study Reservoir quality is a function of effective porosity. area while the lowermost value of effective poros- The high values of effective porosities refer to better ity in adjacent well Kadanwari-10, influenced by the volume estimates and thus theoretically a good reser- structure; further moving southwest of the study area voir and vice versa. the effective porosity increased and estimated high- The effective porosity of zone of interest has been est. PZ-3 characterizes with  12% (Kadanwari-11) computed from neutron porosity and bulk density to 23% (Kadanwari-01); the variograph surface logs. The average values of effective porosities derived (Fig.  5B’) depicts that the effective porosity of the from dual logs was computed. In the absence of core respective zone increases southwest of the study area. data, the empirical methods are reliable to predict the iii. Saturation of water effective reservoir porosity(Asquith et al. 2004).The Indonesian equation (Poupon and Leveaux 1971) is effective porosity has been calculated by notion: one of the effective porosity saturation methods which is applied to calculate S of targeted LGSP; the used Effective porosity =  =  −  × V . equation provides comparatively easy computation E T T sh ND SH (2) and shows numerically positive results (greater than 1 3 1096 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Prospect Zone 2Prospect Zone 3 A´ BB´ CC´ DD´ Fig. 5 Left panel shows the prospect zones 2 and right panel shows prospect zone 3.a Volume of shale, b average effective porosity, c saturation of Hydrocarbons, d thickness 1 3 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 1097 zero). Other quadratic and iterative solution models certainly the gas accumulations of four targeted pros- can calculate negative S which is uncertain. Where pects. the petrophysical traits are the effective porosity, °ϕ , Hydrocarbon bearing zone characterized with high volume and resistivity log reading of 100% shale resistivity values, porosity high, permeability high, (ohm. m) (V and R ) and water resistivity (R ), saturation of water low, and less V suggest clean sh sh w sh deep resistivity log gives true resistivity (R ) at 100% sand. water saturation (ohm. m), cementation factor (m) and v. Permeability (K) saturation exponent (n). The computed results exhibit Permeability estimates provide the unbounded fluid better understanding of shaly sand reservoir (Fig. 4d), flow in porous reservoir, Wyllie–Rose permeability of the selected LGSP was estimated by the following −1 equation: ⎧ ⎡ ⎤⎫ ⎛ m ⎞ � � ⎪ ⎢ ⎥⎪ 2−V sh ⎜ ⎟ V e ⎪ ⎢ ⎥⎪ sh ⎜ ⎟ (3) S = R + . ⎨ ⎢ ⎥⎬ w t K = K . R ⎜ R ⎟ w Sh w ⎪ ⎢ ⎥⎪ S ⎜ ⎟ ⎪ ⎢ ⎥⎪ ⎝ ⎠ ⎩ ⎣ ⎦⎭ We have adopted Morris–Biggs estimates with con- stants d = 6.0, e = 2 and K  = 6500 for gas. The saturation of water within the consolidated Typically, porosity has to exceed 18% and permea- sandstone estimated with the following parameters: bility to be greater than 2 milliDarcy for a sand to pro- tortuosity factor (a = 0.81), cementation exponent duce gas at commercial rates in Kadanwari (Ahmad (m = 2) and saturation exponent (n = 2) (Asquith et al. and Chaudhry 2002). The permeability findings for 2004). Hydrocarbon saturation (S ) is a function of PZ-2 suggest that permeability ranges from ~ 0.7 hc Sw. PZ-2 has S minimum 22% (Kadanweri-03) and Darcy to ~ 4.4 Darcy, whereas for PZ-3 ~ 0.4 Darcy to conversely S 77% which is maximum (southwest of ~ 5.6 Darcy. Quadri and Quadri (1996) suggested the hc study area). Although S for PZ-2 is not lesser than estimation of permeability for lower Goru may exceed hc 31.5%. The interpolated S demonstrates (Fig.  5c) 1 Darcy. hc that hydrocarbon (gas saturation) spatially varies east– west and relatively increases towards southwest of the study area. PZ-3 is characterized with minimum S c. Finally, the thickness distribution maps of PZ-2 (Fig. 5d) hc 36.9% (Kadanwari-11) to 60.9% (Kadanwari-03), and suggest that thickness of gas prone reservoir of LGSP spatially, S increases towards southwestern side of increases in northeast of the study area. The interpolated hc the study area. thickness for PZ-3 (Fig. 5D’) increases southeast of the iv. Hydrocarbon identification study area which ranges with relatively thick packages Furthermore, the delineation of the reservoir zones from 30 to 37 m. has been made through N–D crossover (track-2 of d. The mineral identification (MID) plots are machinated each well, Fig. 4a) and resistivity log analyses (track-3 between photoelectric effect (PEF) and thorium–potas- of each well, Fig.  4a) and the Schlumberger cross- sium ratio (TPRA) which provide ample clue that the plots (Fig.  4b, c). In some conditions, it is claimed reservoir has little dirtiness, encountered in each that there’s a shale rock formation according to high reading for gamma ray, density log and neutron log, but resistivity logs increase; during this circumstance, Conclusion and recommendations the sharp increase in resistivity logs is due to a dia- genetic process such as compaction or cementation The petrophysical studies unearth hydrocarbon potential of and there’s no water content during this condition as four prospect zones (PZ-1 to PZ-4) in Cretaceous age LGF a result of water bearings decrease the resistivity. The which is a productive Kadanwari field. GR index, double separations of resistivity logs (LLD, LLS, MSFL) combo and triple combo plots ascertain sandstone lithology. suggest the presence of hydrocarbon but discrimina- The cross-plots, resistivity separation, and N–D crossover tion between fluid type (oil and gas) at this stage is discriminate gas accumulation. The petrophysical assess- still quizzing. In pursuance, we have utilized N–D ment of reservoir concluded that shallower PZ-1 (11  m plot (Fig. 4b) and M–N plot (Fig. 4c) todiscriminate average thickness) and deepest PZ-4 (30 m avg. thickness), the hydrocarbon type. The rising clusters (reservoir although the intermediate depth zone PZ-2 (18–21 m thick) interval) ascertain least density reservoir pore fluid, and PZ-3 (30–37 m thick) are main prospects of this study. PZ-2 and PZ-3 hold key indicators: low GR, crossover of 1 3 1098 Journal of Petroleum Exploration and Production Technology (2018) 8:1089–1098 Lower and Middle Indus Platform, Pakistan: In: PAPG, Annual density porosity, separation of resistivities, low S , high Technical Conference, p. 85–104 hydrocarbon saturation and favorable permeability. PZ-2 Ahmad N, Spadini G, Palekar A, Subhani MA (2007) Porosity predic- results highlight reservoir sands characterizing V from sh tion using 3D seismic inversion Kadanwari Gas Field, Pakistan. 0.49 to 0.71,  from 0.16 to 0.22, S from 0.22 to 0.68 Pak J Hydrocarb Res 17:95–102 ND w Asquith GB, Krygowski D, Gibson CR (2004) Basic well log analysis, and S 0.31–0.77. PZ-3 results exhibit good quality of res- hc American Association of Petroleum Geologists, Tulsa ervoir sands having more thickness and characterizing V sh Baig MO, Harris N, Ahmed H, Baig M (2016) Controls on reservoir 0.62–0.77,  from 0.12 to 0.23, S from 0.39 to 0.63 and ND w diagenesis in the Lower Goru Sandstone Formation, Lower Indus S 0.36–0.6. Thus, PZ-3 is thick package of sand and shows basin, Pakistan. J Pet Geol 39(1):29–47 hc Dolan P (1990) Pakistan: a history of petroleum exploration and future comparatively better reservoir characteristics. The quanti- potential. Geological Society, London, 50, pp 503–524 fication of petrophysical analysis reveals that the prospect Hussain M, Ahmed N, Chun WY, Khalid P, Mahmood A, Ahmad SR, zones Lower Goru Formation have good potential and sig- Rasool U (2017) Reservoir characterization of basal sand zone nificant accumulation of hydrocarbons and this study will of lower Goru Formation by petrophysical studies of geophysical logs. J Geol Soc India 89(3):331–338 enhance future hydrocarbon exploration and exploitation Kadri IB (1995) Petroleum geology of Pakistan, Pakistan Petroleum activities in parts of lower Indus basin of Pakistan. However, Limited, Karachi results are acquired only based on petrophysical analysis. To Kazmi AH, Jan MQ (1997), Geology and tectonics of Pakistan. strengthen the estimated results, we recommend geochemis- Graphic publishers, Santa Ana Khalid P, Yasin Q, Sohail G, Kashif JM (2015) Integrating core and try data for source rock basic information, core for absolute wireline log data to evaluate porosity of Jurassic formations of reservoir properties, and 3D seismic reflection datasets for Injra-1 and Nuryal-2 wells, Western Potwar, Pakistan. J Geol Soc the development of local play concepts and prospect/lead India 86(5):553 assessments. Based on good quality reservoir characteristics Munir K, Iqbal MA, Farid A, Shabih SM (2011) Mapping the produc- tive sands of Lower Goru Formation by using seismic stratigraphy of PZ-4 (Table 2 and Fig. 4a), it is also recommended to drill and rock physical studies in Sawan area, southern Pakistan: a case all the wells down to this zone in the concession blocks and study. J Pet Explor Prod Technol 1(1):33–42 may invest on this productive zone in the future. Naeem M, Jafri MK, Moustafa SS, AL-Arifi NS, Asim S, Khan F, Ahmed N (2016) Seismic and well log driven structural and petro- Acknowledgements We thank the potential reviewers for their sugges- physical analysis of the Lower Goru Formation in the Lower Indus tions to improve the manuscript. We also thank DGPC for providing Basin, Pakistan. Geosci J 20(1):57–75 necessary data, and acknowledge the moral support of PPL Chair in Poupon A, Leveaux J (1971) Evaluation of water saturation in shaly facilitation of this study in Digital Geophysical Data Lab at Bahria formations. In: Proceedings SPWLA 12th Annual Logging Sym- University Karachi Campus. posium, Society of Petrophysicists and Well-Log Analysts Quadri V-u-N, Quadri S (1996) Anatomy of success in oil and gas exploration in Pakistan, 1915–94. Oil Gas J 94:20 Open Access This article is distributed under the terms of the Crea- Shar AM, Mahesar AA, Memon KR (2017) Could shale gas meet tive Commons Attribution 4.0 International License (http://creat iveco energy deficit: its current status and future prospects. J Pet Explor mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- Prod Technol. https ://doi.org/10.1007/s1320 2-017-0399-y tion, and reproduction in any medium, provided you give appropriate Zaigham NA, Mallick KA (2000) Prospect of hydrocarbon associated credit to the original author(s) and the source, provide a link to the with fossil-rift structures of the southern Indus basin, Pakistan: Creative Commons license, and indicate if changes were made. AAPG Bull, 84(11):1833–1848 Publisher’s Note Springer Nature remains neutral with regard to References jurisdictional claims in published maps and institutional affiliations. Ahmad N, Chaudhry S (2002) Kadanwari gas field, Pakistan: a disap- pointment turns into an attractive development opportunity. Petrol Geosci 8(4):307–316 Ahmad N, Fink P, Sturrock S, Mahmood T, Ibrahim M (2004) Sequence stratigraphy as predictive tool in Lower Goru Fairway, 1 3

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Journal of Petroleum Exploration and Production TechnologySpringer Journals

Published: Jun 4, 2018

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