Shale Volume Research Articles

PETROPHYSICAL ANALYSIS AND SEISMIC STRATIGRAPHY INTERPRETATION TO DETERMINE HYDROCARBON RESERVOIR IN TARAKAN BASIN, BUNYU ISLAND WATERS

Tarakan Basin area of Bunyu Island Waters is known to have hydrocarbon potential with complex geological structures. This study aims to determine reservoir characterization and to obtain prospect of hydrocarbon reservoir zones based on petrophysical and seismic stratigraphy analysis with reference to Well DDS-1 and 2D seismic Line S88. Petrophysical analysis results 3 zones that have potential as hydrocarbon reservoirs. Based on petrophysical quantitative analysis, Zone 1 has values of 52.25% for shale volume, 18.48% for effective porosity, 39.84% for water saturation and 13.03 mD for permeability. Zone 2 has values of 54.66% for shale volume, 10.27% for effective porosity, 40.9% for water saturation and 1.14 mD for permeability. Zone 3 has values of 49.22% for shale volume, 9.33% for effective porosity, 56.33% for water saturation and 0.22 mD for permeability. Out of these three reservoir zones in Well DDS- 1, Zone 1 has the prospect of hydrocarbons which is supported by the net pay value. Based on seismic stratigraphy interpretation, the reservoir zone is correlated to the Tabul Formation, which comprises calcareous clay and limestone.

Gas-generative potential for the post-Messinian megasequence of Nile Delta Basin: a case study of Tao Field, North Sinai Concession, Egypt

The main aim of the article is to evaluate the gas potentiality for the post-Messinian megasequence in TAO Field, North Sinai Concession, offshore Nile Delta Basin. The detailed petrophysical analysis for three deviated wells in the study area (Tao-3 ST1 Well, Tao-5 STA Well and Tao-7 Well) revealed that the Pliocene Kafr El-Sheikh Formation includes eleven gas-bearing zones. These zones were named: A, B, C in Tao-3 ST1 Well and D, E, F in Tao-5 STA Well. In Tao-7 Well, the interesting zones are named G, H, I, J and K. All of these sandy intervals are relatively shallow in depth and differ in thickness between 4 and 56 m. These zones are characterized by shale volume (10%), total porosity (30–40%), effective porosity (30–35%), gas saturation (50–90%), high effective permeability to gas and low permeability to water. The seismic data displayed that listric faults and the associated rollover folds have an important role in forming structural traps for the examined gas-bearing zones in Tao Field and its surroundings. This work revealed that the success rate in discovering new gas prospects within the Pliocene–Pleistocene succession at North Sinai Concession is very high.

Petrophysical Reservoir Characterization of Habiganj Gas Field, Surma Basin, Bangladesh

The previous studies on the petrophysical and volumetric analysis of Habiganj gas field were based on limited well data. As the accuracy of volumetric analysis relies greatly on petrophysical parameters, it is important to estimate them accurately. In this study we analyzed all eleven wells drilled in the Habiganj field to determine the petrophysical parameters. Analysis of the well logs revealed two distinct reservoir zones in this field termed as upper reservoir zone and lower reservoir zone. Stratigraphically, these two reservoir zones are in the Bokabil and Bhuban Formation of Surma Group. Petrophysical analysis shows significant differences between the two zones in terms of petrophysical parameters. Porosity in the upper reservoir zone ranges from 12% to 36%, with an average of 28%. This zone is highly permeable, as indicated by the average permeability of 500 mili Darcy (mD). The average water saturation in this zone is around 18% suggesting high gas saturation. The lower reservoir zone has an average porosity, permeability, and water saturation of 12%, 60mD, and 43%, respectively, indicating poor reservoir quality. An analysis of log motifs indicates that the upper reservoir zone is composed of stacked sands of blocky pattern. The sands in this interval are clean, as indicated by the lower shale volume of 12-15%. The average thickness of this zone is 230m, and the presence of this zone in all the drilled wells suggests high lateral continuity. The lower reservoir zone consists of sand bodies of serrated pattern. The sands have high shale volume and are laterally discontinuous. Overall, the upper reservoir zone has superior petrophysical properties to the lower reservoir zone. Although the reservoir quality of the lower reservoir zone is poorer than that of the upper zone, this zone can be considered as the secondary target for hydrocarbon production. Petrophysical parameters of this study were estimated from all the eleven wells drilled in this field; hence the values are more accurate. The reported values of the petrophysical parameters in this study are recommended to use to re-estimate the reserves in Habiganj field. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(1), 2021, P 1-10

Lithological Study of Mishrif, Rumaila, Ahmadi and Mauddud Formations Using Vp/ Vs Ratio, Acoustic Impedance and Well Logging at Amara Oil Field, Southern Iraq

The lithology of four formations from the Cretaceous period (Mishrif, Rumaila, Ahmadi, and Mauddud) was evaluated using the Acoustic Impedance and Vp/Vs ratio cross plot from Rock Physics Templates. Dipole sonic logs in Am-6-Am-10 well log were used to calculate compression velocity then the estimated shear velocity using Greenberg Castagna equations. RHOB and VP logs were used to calculate Acoustic Impedance. The ratio of Vp/Vs was measured then used with Acoustic Impedance colored by shale volume which is measured from gamma ray log, porosity and water saturation to estimate lithology type of the considered formations using cross plots and rock physics chart in the Techlog software. The lithology of the formations found to be of high porosity limestone alternating with hard limestone layers and the shale volume increases in the Ahmadi formation. The water bearing zone was found in all Formations, this zone is indicted by high Vp/ Vs ratio and low AI. The hydrocarbon bearing zones were indicated by low amount of both Acoustic Impedance and Vp/Vs ratio and this observation was shown in Mishrif and Mauddud formations.

Petrophysical Analysis of ‘Bright’ Field, Onshore Niger Delta

Petrophysical analysis is key to the success of any oil exploration and exploitation work and this task requires evaluation of the reservoir parameters in order to enhance accurate estimation of the volume of oil in place. This research work involves the use of suite of well logs from 4-wells to carry out the petrophysical analysis of ‘Bright’ Field Niger Delta. The approach used includes lithology identification, reservoir delineation and estimation of reservoir parameters. Two sand bodies were mapped across the entire field showing their geometry and lateral continuity, gamma ray and resistivity logs were used to delineate the reservoirs prior to correlation and relevant equations were used to estimate the reservoir parameters. The result of the petrophysical analysis showed variations in the reservoir parameters within the two correlated sand bodies with high hydrocabon saturation in sand 1 well 1 while the remaining wells within the correlated wells are water bearing. The porosity values range from 0.19 to 0.32, volume of shale from 0.15 to 0.40, water saturation from 0.20 to 0.92 for the sand bodies.

Seismic interpretation, reservoir characterization, gas origin and entrapment of the Miocene-Pliocene Mangaa C sandstone, Karewa Gas Field, North Taranaki Basin, New Zealand

The Karewa gas discovery highlighted the potential for commercial gas accumulations in the shallow Miocene-Pliocene stratigraphic horizons, thus changing the exploration strategy in Taranaki Basin, New Zealand. The gas origin, its entrapment mechanism, and the petrophysical characteristics of the Miocene-Pliocene Mangaa C sandstone reservoir have been evaluated. Organic geochemical analyses of Mangaa and Giant Foresets shales bounding the sandstone reservoir point to their immaturity (Tmax< 426 °C) and poor capability for thermogenic hydrocarbon generation. Karewa gas displays an isotopic pattern of δ13C1 ≫ δ13C3 > δ13C2 reflecting its biogenic origin with no signs of thermogenic input. Additionally, the depleted δ13C1 (of range −61.32% to −61.02%) and δDC1 values (of range −183.5% to −182.3%) support its microbial origin likely by bacterial carbonate reduction and degradation of the organically-bound CO2 to form methane. Shales of the Giant Foresets and Mangaa formations contain, and therefore contain abundant organically-bound CO2.Karewa prospect as a roll-over structure bounded by listric faults forming a four-way dip closure. These faults are the gas migration paths from Mangaa and Giant Forests shales to the Mangaa C sandstone reservoir. Excellent petrophysical reservoir characteristics of Mangaa C sandstone (visual porosity av. 20.7%, helium porosity from core av. 30.2%, shale volume av. 6.4%, and water saturation av. 34.5%) prompted its gas potential with high hydrocarbon saturation (av. 65.5%). Mild mechanical compaction and low content of authigenic mineral phases aided in the preservation of the primary intergranular porosity. Seal capacity analysis of the Mangaa C system confirmed the efficiency of the overlying mudstones to seal a thick gas column (up to 150 m) with a minimal risk of leakage.

Petrophysical properties of bypassed Cenozoic clastic reservoirs in the Cesar sub-basin, Colombia

The Cesar-Ranchería basin has all the necessary elements for the generation, expulsion, and migration of hydrocarbons and considerable potential for coal bed methane (CBM) in Colombia. Previous studies in the Cesar basin focused on understanding the tectonic evolution, stratigraphy, hydrocarbon generation potential, and evaluation of reservoir potential in Cretaceous calcareous units and quartzose sandstones from the Paleocene Barco Formation. These studies had confirmed the existence of an effective petroleum system, with several episodes of oil expulsion and re-emigration in the Miocene period, turning the Cenozoic clastic succession (Barco, Los Cuervos, La Loma, and Cuesta formations) into an element of significant exploratory interest to clarify the potentiality of the basin in terms of hydrocarbon accumulation. The petrophysical parameters of Cenozoic units (shale volume, porosity, water, and oil saturation) were determined by integrating wells log and core samples analyses from three stratigraphic wells. The integration of these results synthesizes the petrophysical behavior of the units. It defines intervals with clay volumes of less than 30%, effective porosity around 20%, which means favorable characteristics as reservoir rocks that need to be considered in future exploratory projects.

Petrophysical modeling in the absence of core data in a small, marginal field in the Mumbai Offshore Basin, India

The best petrophysical models are based on direct measurements from the core. Unfortunately, core is not available in many cases, either for economic, logistical, or historical reasons. In this study, we needed to construct a detailed Field Development Plan (FDP) for the small, marginal B-9 field in the Western Offshore Basin, India, which did not merit core acquisition. The objective is to propose a workflow for building a petrophysical model with limited data sets instead of a typical FDP workflow. After analyzing the assumptions, limitations, and uncertainties involved in the petrophysical model, we used advanced petrophysical logs to reduce uncertainty and create a robust petrophysical model. We carried out a log-based petrophysical study to determine the volume of shale, porosity, saturation, and permeability. The advanced petrophysical logs including spectroscopy, nuclear magnetic resonance (NMR), formation pressures, and well testing data are used to calibrate the petrophysical model. Spectroscopy data are used to calibrate the mineralogical volumes and grain density, whereas the porosity is calibrated from NMR data. We calibrated log-derived permeability results with NMR permeability and mobility from well test data. We used heterogeneous rock analysis on petrophysical outputs to carry out petrophysical rock typing (PRT). This has helped in establishing the porosity-permeability relationship and saturation-height model for each PRT. In the absence of irreducible water saturation ([Formula: see text]) information from the core, NMR-derived [Formula: see text] is calculated and then used to calibrate the saturation model. Log-derived permeability and saturation are estimated, which agrees well with the available testing data. This provided a robust petrophysical model that served as a basis for geologic static and reservoir dynamic models. The gas-down-to and water-up-to methods are used to establish the contacts. The resulting saturation height model agreed well with the saturations derived from the log, which gave us confidence in our dynamic model.

Multi-Objective Optimization of CO2 Sequestration in Heterogeneous Saline Aquifers under Geological Uncertainty

This paper presents a Pareto-based multi-objective optimization for operating CO2 sequestration with a multi-well system under geological uncertainty; the optimal well allocation, i.e., the optimal allocation of CO2 rates at injection wells, is obtained when there is minimum operation pressure as well as maximum sequestration efficiency. The distance-based generalized sensitivity analysis evaluates the influence of geological uncertainty on the amount of CO2 sequestration through four injection wells at 3D heterogeneous saline aquifers. The spatial properties significantly influencing the trapping volume, in descending order of influence, are mean sandstone porosity, mean sandstone permeability, shale volume ratio, and the Dykstra–Parsons coefficient of permeability. This confirms the importance of storable capacity and heterogeneity in quantitatively analyzing the trapping mechanisms. Multi-objective optimization involves the use of two aquifer models relevant to heterogeneity; one is highly heterogeneous and the other is less so. The optimal well allocations converge to non-dominated solutions and result in a large injection through one specific well, which generates the wide spread of a highly mobile CO2 plume. As the aquifer becomes heterogeneous with a large shale volume and a high Dykstra–Parsons coefficient, the trapping performances of the combined structural and residual sequestration plateau relatively early. The results discuss the effects of spatial heterogeneity on achieving CO2 geological storage, and they provide an operation strategy including multi-objective optimization.

Study of Petrophysical Properties of the Yamama Formation in Siba Oilfield

Evaluating a reservoir to looking for hydrocarbon bearing zones, by determining the petrophysical properties in two wells of the Yamama Formation in Siba field using Schlumberger Techlog software. Three porosity logs were used to identify lithology using MN and MID cross plots. Shale volume were calculated using gamma ray log in well Sb-6ST1 and corrected gamma ray in well Sb-5B. Sonic log was used to calculate porosity in bad hole intervals while from density log at in-gauge intervals. Moreover, water saturation was computed from the modified Simandoux equation and compared to the Archie equation. Finally, Permeability was estimated using a flow zone indicator. The results show that the Yamama Formation is found to be mainly limestone that confirmed by cuttings description and this lithology intermixed with some dolomite, in addition to gas and secondary porosity effects. Generally, the formation is considered clean due to the low shale volume in both wells with the elimination of the uranium effect in well Sb-5B. The calculated porosity was validated by core porosity in YC and YD units. Modified Simandoux gives a better estimation than the Archie equation since it takes into account the conductive of matrix in addition to the fluid conductivity. Five equations were obtained from porosity permeability relationship of core data based on five hydraulic flow units reorganized from the cross plot of reservoir quality index against normalized porosity index. The overall interpretation showed that YC and YD units are the best quality hydrocarbon units in the Yamama Formation, while YA came in the second importance and has properties better than YB. Moreover, YE and YFG are poor units due to high water saturation.

Petrophysical Evaluation of Mauddud Formation in Selected Wells from Ratawi Oil Field, Southern Iraq

The objective of this paper is determining the petrophysical properties of the Mauddud Formation (Albian-Early Turonian) in Ratawi Oil Field depending on the well logs data by using interactive petrophysical software IP (V4.5). We evaluated parameters of available logs that control the reservoir properties of the formation, including shale volume, effective porosity, and water saturation. Mauddud Formation is divided into five units, which are distinguished by various reservoir characteristics. These units are A, B, C, D, and E. Through analyzing results of the computer processed interpretation (CPI) of available wells, we observed that the main reservoir units are B and D, being distinguished by elevated values of effective porosity (10%-32%) and oil saturation (95%-30%) with low shale content (6%-30%). Whereas, units A, C, and E were characterized by low or non-reservoir properties, due to high water saturation and low values of effective porosity caused by increased volume shale.

Geophysical assessment and hydrocarbon potential of the Cenomanian Bahariya reservoir in the Abu Gharadig Field, Western Desert, Egypt

In this study, the sandstones of the Bahariya Formation in the Abu Gharadig Field, which is a promising oil reservoir in the Abu Gharadig Basin, Western Desert, Egypt, were assessed. The wireline logs from three wells (Abu Gharadig-2, Abu Gharadig-6, and Abu Gharadig-15) were studied using seismic and petrophysical analyses. Based on seismic data, the study area contains an ENE–WSW anticlinal structure, which is divided by a set of NW–SE normal faults, reflecting the effect of Late Cretaceous dextral wrench tectonics on the northern Western Desert. The visual analysis of the well logs reveals a potential zone within well Abu Gharadig-2 located between depths of 10,551 and 10,568 ft (zone A). In contrast, potential zones were detected between depths of 11,593–11,623 ft (zone B) and 11,652–11,673 ft (zone C) in well Abu Gharadig-6. In well Abu Gharadig-15, potential zones are located between depths of 11,244–11251ft (zone D) and 11,459–11,467 ft (zone E). The quantitative evaluation shows that the intervals B and C in well AG-6 are the zones with the highest oil-bearing potential in the Abu Gharadig Field in terms of the reservoir quality. They exhibit the lowest shale volume (0.06–0.09), highest effective porosity (0.13), minimum water saturation (0.11–0.16), lowest bulk volume of water (0.01–0.02), high absolute permeability (10.92–13.93 mD), high relative oil permeability (~ 1.0), and low water cut (~ 0). The apex of the mapped fold represents that the topmost Bahariya Formation in the Abu Gharadig Field for which the drilling of additional wells close to well AG-6 is highly recommended.

Effect of reservoir heterogeneities on elastic and seismic properties of Lower Cretaceous Sand Intervals, Lower Indus Basin of Pakistan

The use of rock physics modeling and petrophysical analysis has become an integral part of quantitative seismic interpretation. In the present study, the above-mentioned techniques are applied to the reservoir interval of Basal Sand of Cretaceous age widely distributed in the Lower Indus Basin of Pakistan. The data used for this purpose consists of complete suits of wireline logs from four well A, B, C and D. The primary goal of this work is to understand the trends of seismic parameters such as P-wave velocity (VP), S-wave velocity (VS), bulk modulus, bulk density as a function of fluid saturation and porosity in this sand interval. Petrophysical analysis based on well logs is used to obtain petrophysical properties such as porosity, the volume of shale, fluid saturation, P-wave velocity (VP), S-wave velocity (VS) and density at reservoir conditions. The results show that seismic parameters are very sensitive to fluid saturation, fluid types and rock-forming sediments. Reservoir porosity and fluid saturation control the elastic response of Basal Sand due to which seismic velocities decrease with an increase in porosity and fluid saturation.

Petrophysical characterization for Thebes and Mutulla reservoirs in Rabeh East Field, Gulf of Suez Basin, via well logging interpretation

The current work assesses the sandstones of the Mutulla Formation as well as the limestone of the Thebes Formation for being promising new oil reservoirs in Rabeh East field at the southern portion of the Gulf of Suez Basin. This assessment has been achieved through petrophysical evaluation of wireline logs for three wells (RE-8, RE-22 and RE-25). The visual analysis of well logs data revealed that RE-25 Well is the only well demonstrating positive criteria in five zones for being potential oil reservoirs. The favourable zone within Thebes Formation locates between depths 5084 ft and 5100 ft (Zone A). However, the other positive zones in Mutulla Formation occur between depths: 5403.5–5413.5 ft (Zone B), 5425.5–5436 ft (Zone C), 5488–5498 ft (Zone D) and 5558.5–5563.5 ft (Zone E). The quantitative evaluation shows that the Zone A of Thebes Formation is the best oil-bearing zone in RE-25 Well in terms of reservoir quality since it exhibits lowest shale volume (0.07), minimum water saturation (0.23) and lowest bulk volume of water (0.03). These limestone beds include type of secondary porosity beside the existing primary porosity. On the other hand, the sandstones of Mutulla Formation in RE-25 contain four reservoir zones (B, C, D and E) with the total net pay thickness of 35.5 ft. Moreover, the obtained results revealed that it is expected for zones B, C and D to produce oil without water but Zone E will produce oil with water.

Petrophysical evaluation of sandstone gas reservoir using integrated well logs and core data for the Lower Cretaceous Kharita formation, Western Desert, Egypt

This study aims to evaluate Kharita gas reservoir to enhance the production. The increase in water-cut ratio reduces the left hydrocarbons’ amount behind pipe. Accurate determination of pore throats, pores connectivity and fluid distribution are central elements in improved reservoir description. The integration of core and logging data responses is often used to draw inferences about lithology, depositional sequences, facies, and fluid content. These inferences are based on petrophysical models utilizing correlations among tools’ responses as well as rocks and fluids properties. Upper Kharita Formation produces gas and condensate from the clastic sandstone in Badr-3 field, western desert of Egypt. It consists mainly of sandstone with shale intercalations. It is subdivided into three sub-units Kharita A, Kharita B and Kharita C that are in pressure communication. Hence, a new further investigation and review for the previously calculated GIIP (gas initially in place) was initiated. The results of this study yielded that the main uncertainty in the volumetric calculations was the petrophysical evaluation; subsequently, a new unconventional petrophysical evaluation approach was performed. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. The sands thickness in Upper Kharita Formation varies between more than 9 up and more than 61 m with average porosity values range between 0.08 and 0.17 PU while the average permeability values range between 1.89 and 696.66 mD. The average hydrocarbon saturation values range between 46 and 97%. Reservoir shale cutoff of 55% by using cross-plot between shale volume and porosity (Toby Darling concept) was utilized to discriminate the reservoir from non-reservoir sections. The porosity model was used to calculate reservoir porosity, using the density log. The Archie and saturation/height function models were used to calculate the water saturation and used to calibrate the water saturation in the transition zone. The porosity–permeability (POR-PERM) transform equation was used to estimate the reservoir connectivity (absolute permeability) for the four petrophysical facies (High Quality Reservoir, Moderate Quality Reservoir, Low Quality Reservoir and Highly Shale Reservoir). Core data have shown variations in reservoir quality parameters (porosity and permeability) from one well to the other. Integration of all the reservoir pressures indicated that there are different fluid types (oil, gas and water) in the Upper Kharita Formation level. The saturation/height function model was used to calibrate the saturation in the transition zone. The integration of geological core and geophysical log data helped to conduct a comprehensive petrophysical assessment of Upper Kharita Formation for a better estimation of the reservoir and to achieve a better understanding of the water encroachment in the Upper Kharita reservoir. The big challenge is the determination of the most correct model for calculating porosity, permeability and water saturation in this reservoir of different quality sand. The new petrophysical evaluation resulted in doubling the volumes in Upper Kharita reservoir and so a perforation campaign was performed to confirm the new volumetric calculations, which showed a good match with the model results. Hence, a new well was drilled targeting the low quality sand and found them with high pressure almost near virgin pressure.

K-Mean Clustering Analysis and Logistic Boosting Regression for Rock Facies Characterization and Classification in Zubair Reservoir in Luhais Oil Field, Southern Iraq

Identifying rock facies from petrophysical logs is a crucial step in the evaluation and characterization of hydrocarbon reservoirs. The rock facies can be obtained either from core analysis (lithofacies) or from well logging data (electrofacies). In this research, two advanced machine learning approaches were adopted for electrofacies identification and for lithofacies classification, both given the well-logging interpretations from a well in the upper shale member in Luhais Oil Field, southern Iraq. Specifically, the K-mean partitioning analysis and Logistic Boosting (Logit Boost) were conducted for electrofacies characterization and lithofacies classification, respectively. The dataset includes the routine core analysis of core porosity, core permeability, and measured discrete lithofacies along with the well-logging interpretations include (shale volume, water saturation and effective porosity) given the entire reservoir interval. The K-Mean clustering technique demonstrated good matching between the vertical sequence of identified electrofacies and the observed lithofacies from core description as attained 89.92% total correct percent from the confusion matrix table. The Logit Boost showed excellent matching between the recognized lithofacies from the core description and the predicted lithofacies through attained 98.26% total correct classification rate index from the confusion matrix table. The high accuracy of the Logit Boost algorithm comes from taking into account the non-linearity between the lithofacies and petrophysical properties in the classification process. The high degree of lithofacies classification by Logit Boost in this research can be considered in a similar procedure at all sandstone reservoirs to improve the reservoir characterization. The complete facies identification and classification were implemented with the programming language R, the powerful open-source statistical computing language.

Enhanced group method of data handling (GMDH) for permeability prediction based on the modified Levenberg Marquardt technique from well log data

Permeability is the key variable for reservoir characterization used for estimating the flow patterns and volume of hydrocarbons. Modern computer advancement has highlighted the use of machine learning approaches such as group method of data handling (GMDH) in predicting permeability. However, the widely employed GMDH has intrinsic problems in its application. Therefore, the objective of this study is to present an enhanced GMDH based modified Levenberg-Marquardt (LM) as an improved alternative to conventional GMDH in predicting permeability from well logs. The study used natural gamma-ray, standard resolution formation density, limited effective porosity, shale volume of rock, and thermal neutron porosity well logs as input variables. Results show that an enhanced method has a reasonable reduction in processing time with high accuracy. Compared to conventional GMDH and backpropagation neural networks (BPNN), the GMDH-LM used 30% less computation time and performed excellently during training with the least error values of 0.092 and 0.018 for RMSE and MAE. Likewise, good results were observed during testing, obtaining the least error values of 0.679 and 0.056 for RMSE and MAE respectively. The modified generalization performance of GMDH-LM makes it an improved form of GMDH and can be adopted as an improved alternative in predicting permeability.

Implication of well logs for evaluation of a carbonate reservoir: an example, the Sarvak Formation, Zagros Basin, SW Iran

Petrophysical evaluation of well log data of the Mid Cretaceous rocks (Upper part of the Sarvak Formation) were conducted for the Marun oil field. Rock and fluid volumetric indices, such as porosity type and distribution, water saturation, and lithology, were estimated from density, resistivity, neutron porosity, sonic and gamma ray logs. Petrophysical parameters including shale volume (Vsh), total porosity (PHT), effective porosity (PHE), water saturation (Sw), hydrocarbon saturation (Sh) and lithology were calculated. Matrix Identification (MID), M-N, NPHI- RHOB, NPHI- DT cross-plots indicated that the Sarvak Formation is mainly composed of carbonate lithology. Results also indicated that shale volume varies between 0.1% and 23.3%; total and effective porosities are between 0.8% and 47.2% and between 0.1% and 45.1%, respectively. Various primary and secondary porosities do exist in the Sarvak Formation. Majority of the porosities are preferentially developed in the middle part of this oil field. Water saturation is between 2% and 100%. The results reveal that the reservoir characterization of the Sarvak Formation is very variable and fluctuating from poor to good reservoir units. Apparently, Sw increase toward the center of the reservoir and eastward as well. This is probably in part controlled by fractures that are preferentially concentrated in the middle part of the anticline.

Lithology Identification, Shale Volume Estimation and Formation Wate Saturation of Fenchuganj Gas Field Using Wireline Log Data

This study has been undertaken with a view to interpreting and analyzing different types of logs, detecting hydrocarbon-bearing sand zone, identifying the lithology, estimating shale volume, and determining water saturation of the formation of the Fenchuganj gas field. Fenchuganj gas field is in the southern part of Bangladesh in the Sylhet division. It lies in the Surma basin and characterized as a water drive gas field. Gamma Ray (GR) log and Spontaneous Potential (SP) log analysis help to interpret the formation lithology. After interpreting lithology, the gamma-ray log and SP log were analyzed further, and the hydrocarbon-bearing zone was detected. From the analysis of different logs, for well 4, so many gas-bearing sand zones have been detected. The gas-bearing zones are found between (1585-1595) m, (1600-1610) m, (2409-2420) m, (2265-2270) m, (2295-2303) m, (2435-2450) m, (2465-2480) m, (3150-3155) m, (2955- 2960) m. These are the gas-bearing zones of fenchugonj well-4 determined from the composite log of this field. Water-bearing sand zones are between (1708-1714) m and the fully compacted shale zone is between (1920-1930) m. From the analysis of different logs, for well 5, so many gas-bearing sand zones have been detected. The gas-bearing zones are found between (2365-2385.5) m, (1820-1830) m, (1782-1803) m, (305-308) m, (336.5-338.5) m, (607.5-609.5) m. These are the gas-bearing zone of fenchugonj well-5 determined from the composite log of the field. Shale volume has been estimated from the gamma-ray log and from resistivity logs by the true resistivity method. In well 4, the calculated value of shale volume by Gamma Ray method and true Resistivity methods were respectively 15% and 6%, in well 5 these values were 7.25% and 7.64%. Formation water resistivity was determined from the formula and taken as 0. 1ohm-m and mud filtrate resistivity 0.76 ohm-m. for well-4 and for well-5 it was taken as 0.7 ohm-m (from the provided composite log of well 4 and 5). Formation true resistivity Rt was estimated directly from the ILD log and true resistivity log. The average value of Rt for well-5 was 33.75 ohm-m and for well-4 the value is 34.09 ohm-m. From the RFOC log, flushed zone resistivity Rxo was calculated directly. Water saturation has been determined by three different techniques named Archie, Indonesia, and Simandoux method. For well 5, the value of average water saturation found from Archie, Indonesia, and Simandoux model was 8.5%,22%, and 24.84%, and for well-4. The value of average water saturation was found as 7.3%,18%, 20.51%respectively.

Modeling of the Shale Volume in the Hendijan Oil Field Using Seismic Attributes and Artificial Neural Networks

AbstractPetrophysical properties have played an important and definitive role in the study of oil and gas reservoirs, necessitating that diverse kinds of information are used to infer these properties. In this study, the seismic data related to the Hendijan oil field were utilised, along with the available logs of 7 wells of this field, in order to use the extracted relationships between seismic attributes and the values of the shale volume in the wells to estimate the shale volume in wells intervals. After the overall survey of data, a seismic line was selected and seismic inversion methods (model‐based, band limited and sparse spike inversion) were applied to it. Amongst all of these techniques, the model‐based method presented the better results. By using seismic attributes and artificial neural networks, the shale volume was then estimated using three types of neural networks, namely the probabilistic neural network (PNN), multi‐layer feed‐forward network (MLFN) and radial basic function network (RBFN).