Petrophysical Evaluation Research Articles

Siamese-SR: A Siamese Super-Resolution Model for Boosting Resolution of Digital Rock Images for Improved Petrophysical Property Estimation

Digital Rock Physics leverages advances in digital image acquisition and analysis techniques to create 3D digital images of rock samples, which are used for computational modeling and simulations to predict petrophysical properties of interest. However, the accuracy of the predictions is crucially dependent on the quality of the digital images, which is currently limited by the resolution of the micro-CT scanning technology. We have proposed a novel Deep Learning based Super-Resolution model called Siamese-SR to digitally boost the resolution of Digital Rock images whilst retaining the texture and providing optimal de-noising. The Siamese-SR model consists of a generator which is adversarially trained with a relativistic and a siamese discriminator utilizing Materials In Context (MINC) loss estimator. This model has been demonstrated to improve the resolution of sandstone rock images acquired using micro-CT scanning by a factor of 2. Another key highlight of our work is that for the evaluation of the super-resolution performance, we propose to move away from image-based metrics such as Structural Similarity (SSIM) and Peak Signal to Noise Ratio (PSNR) because they do not correlate well with expert geological and petrophysical evaluations. Instead, we propose to subject the super-resolved images to the next step in the Digital Rock workflow to calculate a crucial petrophysical property of interest, viz. porosity and use it as a metric for evaluation of our proposed Siamese-SR model against several other existing super-resolution methods like SRGAN, ESRGAN, EDSR and SPSR. Furthermore, we also use Local Attribution Maps to show how our proposed Siamese-SR model focuses optimally on edge-semantics, which is what leads to improvement in the image-based porosity prediction, the permeability prediction from Multiple Relaxation Time Lattice Boltzmann Method (MRTLBM) flow simulations as well as the prediction of other petrophysical properties of interest derived from Mercury Injection Capillary Pressure (MICP) simulations.

Petrophysical experiment-based evaluation method for the saturation of gas hydrate

The seas around China contain abundant non-diagenetic gas hydrate deposits. The traditional logging and evaluation techniques based on conventional oil and gas no longer satisfy the evaluation requirements of offshore gas hydrate layers, and it remains difficult to calculate the hydrate saturation accurately, which seriously restricts the accurate evaluation of the resources. Petrophysical experiments are an important means to study gas hydrate. By simulating the hydrate formation conditions in sediments under natural conditions, the study of various petrophysical properties of gas hydrate is essential to the exploration and development of hydrates and the prediction of reservoir parameters. In this study, a tetrahydrofuran (THF) solution, montmorillonite, and natural sea sand were selected to simulate the growth of gas hydrate based on its characteristics in the study area, and in situ CT scanning experiments were carried out at different hydrate formation stages to determine the microscopic morphologies of gas hydrates within the pore space. In addition, the acoustic wave and resistivity of hydrates with different saturations were measured. Forward modeling of a differential effective medium (DEM) model was conducted for the hydrate reservoirs with different saturations, and the gas hydrate morphology was analyzed. Thereafter, the hydrate saturation predictions based on the petrophysical experiments were analyzed. The results of these analyses indicate that the microscopic morphology of hydrates in the study area is primarily pore-filling form. Based on the saturation estimations using the Archie's law, Wood equation, time-average equation and the DEM method, and under the constraint of the acoustic and electrical measurement results of the petrophysical experiments, an electric acoustic joint model was built by integrating the resistivity and acoustic waves. The estimation results indicate that the joint electro–acoustic model is the best method for calculating the saturation in the study area. • Design of experiments to simulate gas hydrate generation with THF, montmorillonite, and natural sea sand. • Multiple hydrate saturation prediction methods based on acoustic, electrical, and petrophysical models. • Determination of microscopic morphologies of gas hydrate. • A joint acoustic and resistivity hydrate saturation prediction model based on hydrate petrophysical experiments.

Evaluation of the Influence of Shale on the Petrophysical Properties of Hydrocarbon-Bearing Reservoir Sand in “CAC” Field in the Niger Delta, Nigeria

This study aims at evaluating the influence of the presence of shale on the quality of reservoir sand in “CAC-Field”, Coastal swamp Niger Delta by integrating suites of well logs and 3D pre-stack seismic data. Shales in the reservoir pose interpretation challenges as they form baffles to fluid flow and reduce effective porosity. The data used included well logs (density, gamma ray, neutron, resistivity) and 3D seismic data. Petrel and Interactive Petrophysics software were adopted for the analyses. The Vclay/effective porosity cross-plots were used to determine the clay distribution patterns hence the influence of shale on the petrophysical properties of the hydrocarbon reservoir. Result of the well correlation yielded 12 reservoirs with 4 (RES 4 - RES 7) being hydrocarbon bearing and laterally continuous across the 4 wells, (CAC-1 - CAC-4) forming the focus of the study. Evidence of an NW-SE trending delta progradation in the CAC field is represented by the increasing sandiness downdip, at both intermediate and the shallow horizons. Thickening of the reservoir in some instances may be structurally controlled due to faulting. The results from the petrophysical evaluation show Vclay ranges of 13% - 21% and good to very good porosity values that vary from 15% - 25%. The permeability range from 240.49 - 2406.49 mD except for the sands in RES 7, CAC-3 well where the permeability was low (91 mD). Additionally, the Vclay/Effective Porosity cross-plots indicate essentially laminated and structural clay types with few dispersed clay in RES 7, CAC-3 well. The existence of these 3 clay types did not significantly influence the quality of the sands containing the hydrocarbon in the area, except in RES 7, CAC-3. The compartmentalizing effect of the laminated clay/shale could only possibly affect the vertical flow due to possible baffles to the vertical flow, but the horizontal flow may not have been impeded significantly. The study of the type and pattern of clay has helped to better evaluate the quality and mobility trend of the hydrocarbon in the CAC field.

Determination of Reservoir Quality in Field “D” in Central Niger Delta, Using Well Log Data

Well log data was used in this study to assess reservoir properties of field "D" in the southern area of the Niger Delta. For successful petrophysical evaluation, three hydrocarbon-bearing reservoirs (reservoirs A, B, and C) were identified and correlated. The following metrics were tested to determine reservoir properties: porosity, permeability, shale volume, fluid saturation, and net pay thickness. The calculated reservoir property values indicate high reservoir quality. Porosity readings in well OTIG 2 are almost the same, averaging 20%, but values in wells OTIG 7 and OTIG 9 vary from 14-20%. The reservoirs' average permeability was greater than 100md. However, in wells OTIG 2 and OTIG 9, values steadily decline with depth due to compaction caused by the overburden pressure of the underlying rock. Hydrocarbon saturation values in well OTIG 2 are almost the same, averaging 60%, but vary from 60-70% in well OTIG 7 as well as 48-55% in well OTIG 9. Water saturation values in well OTIG 2 are almost the same, averaging 40%, but range from 30-40% in well OTIG 7 and 45-52% in well OTIG 9. The average bulk volume water values in well OTIG 2 are almost the same, averaging 8%, but range from 6-8% in well OTIG 7 and 7-9% in well OTIG 9. There is some evidence that reservoirs A, B, and C in well OTIG 2 are one continuous sand body. This is due to the fact that their porosity, bulk volume water, hydrocarbon saturation, and water saturation values are all roughly the same, and their depth values are all quite similar. The bulk volume water values support the hypothesis that these formations are homogeneous and near irreducible water saturation. The reservoirs found in the field contain hydrocarbons.

A method for determining fluids contact and identifying types of reservoir fluids in the F3-sandstone reservoir, field case study in Libya

This research study focuses on the use of tools for well X05-NC169a in (X field) in Libya. Tools such as reservoir saturation tool and repeat formation tool used in this study. F3-Sand Stone is the main reservoir and has a gross thickness ranging from 130 to 187 feet. The aim of this study is to identify the type of fluid and to determine fluid contacts in the F3 - Sand Stone Reservoir. The study was based on a petro-physical evaluation on the well X05-NC169a by using log data (Gamma Ray Log, Resistivity Log, Neutron Log and Density Log). The Techlog software was used to analyze the log data, while the Surfer software was used for mapping. The results indicate that it has a hydrocarbon and water column. Apart from combining the petro-physical results of well tests ( RFT data and RST) is to define the reservoir fluids type. The fluid contacts changed when the hydrocarbon fluid level decreased. The most dominant Hydrocarbon in the reservoir, according to RFT, RST, and Petro-physics data, is predominantly two phases. Zones of gas and oil.

An Integrated Petrophysical Characterization of a Siliciclastic Tight Gas Reservoir in Neuquén Basin, Western Argentina

The Río Neuquén Field is located between Neuquén and Río Negro provinces, Argentina. Historically, it has been a conventional oil producer, but it was converted to a tight gas producer from deeper reservoirs. The targeted geological formations are Lajas, which is already a known tight gas producer, and the less-known overlaying Punta Rosada Formation, which is the main objective of the current work. Punta Rosada presents a diverse lithology, including shaly intervals separating multiple stacked reservoirs that grade from fine-grained sandstones to conglomerates. The reservoir pressure can change from the normal hydrostatic gradient to up to 50% of overpressure. There is little evidence of movable water. The key well in this study has a comprehensive set of openhole logs, including pulsed-neutron spectroscopy data, and is supported by a full core study over 597 ft. Additionally, data from several offset wells were used, containing sidewall cores and complete sets of electrical logs. This allowed the development of rock-calibrated mineral models, adjusting the clay volume with X-ray diffraction data, porosity, and permeability with core measurements, and linking the log interpretation to dominant pore-throat radius models from MICP Purcell tests. Several water saturation models were tested, attempting to adjust the irreducible water saturation with NMR and Purcell tests at reservoir conditions. As a result, three hydraulic units were defined and characterized, identifying a strong correlation with lithofacies observed in cores and image logs. A cluster analysis model allowed the propagation of the facies to the rest of the wells (50). Finally, lithofacies were distributed in a full-field 3D model, guided by an elastic seismic inversion. In the main key well, in addition to the openhole logs and core data, a casedhole pulsed-neutron log (PNL) was also acquired, which was used to develop algorithms to generate synthetic pseudo-openhole logs such as bulk density and resistivity, integrated with the spectroscopy mineralogical information and other PNL data, to perform the petrophysical evaluation. This enables the option to evaluate wells in contingency situations where openhole logs are not possible or too risky, and also in planned situations to replace the openhole data in infill wells, saving considerable drilling rig time during this field development phase. Additionally, the calibrated casedhole model can be used in old wells. This paper explores the integration of different core and log measurements and explains the development of rock-calibrated petrophysical and rock type models addressing the characterization challenges found in tight gas sand reservoirs. The results of this study will be crucial to optimize the field development.

The benefits and dangers of using artificial intelligence in petrophysics

Artificial Intelligence, or AI, is a method of data analysis that learns from data, identify patterns and makes predictions with the minimal human intervention. AI is bringing many benefits to petrophysical evaluation. Using case studies, this paper describes several successful applications. The future of AI has even more potential. However, if used carelessly there are potentially grave consequences. A complex Middle East Carbonate field needed a bespoke shaly water saturation equation. AI was used to ‘evolve’ an ideal equation, together with field specific saturation and cementation exponents. One UKCS gas field had an ‘oil problem’. Here, AI was used to unlock the hidden fluid information in the NMR T1 and T2 spectra and successfully differentiate oil and gas zones in real time. A North Sea field with 30 wells had shear velocity data (Vs) in only 4 wells. Vs was required for reservoir modelling and well bore stability prediction. AI was used to predict Vs in all 30 wells. Incorporating high vertical resolution data, the Vs predictions were even better than the recorded logs. As it is not economic to take core data on every well, AI is used to discover the relationships between logs, core, litho-facies and permeability in multi-dimensional data space. As a consequence, all wells in a field were populated with these data to build a robust reservoir model. In addition, the AI predicted data upscaled correctly unlike many conventional techniques. AI gives impressive results when automatically log quality controlling (LQC) and repairing electrical logs for bad hole and sections of missing data. AI doesn’t require prior knowledge of the petrophysical response equations and is self-calibrating. There are no parameters to pick or cross-plots to make. There is very little user intervention and AI avoids the problem of ‘garbage in, garbage out’ (GIGO), by ignoring noise and outliers. AI programs work with an unlimited number of electrical logs, core and gas chromatography data; and don’t ‘fall-over’ if some of those inputs are missing. AI programs currently being developed include ones where their machine code evolves using similar rules used by life’s DNA code. These AI programs pose considerable dangers far beyond the oil industry as described in this paper. A ‘risk assessment’ is essential on all AI programs so that all hazards and risk factors, that could cause harm, are identified and mitigated.

Hydrocarbon Reservoir Characterization of ‘Khume’ Field, Offshore Niger Delta, Nigeria

The integrative approach of well log correlation and seismic interpretation was adopted in this study to adequately characterize and evaluate the hydrocarbon potentials of Khume field, offshore Niger Delta, Nigeria. 3-D seismic data and well logs data from ten (10) wells were utilized to delineate the geometry of the reservoirs in Khume field, and as well as to estimate the hydrocarbon reserves. Three hydrocarbon-bearing reservoirs of interest (D-04, D-06, and E-09A) were delineated using an array of gamma-ray logs, resistivity log, and neutron/density log suites. Stratigraphic interpretation of the lithologies in Khume field showed considerable uniform gross thickness across all three sand bodies. Results of petrophysical evaluations conducted on the three reservoirs correlated across the field showed that; shale volume ranged from 7-14%, total and effective porosity ranged from 19-26% and 17-23% respectively, NTG from 42 to 100%, water saturation from 40%-100% and permeability from 1265-2102 mD. Seismic interpretation established the presence of both synthetic and antithetic faults. A total of six synthetic and four antithetic faults were interpreted from the study area. Horizons interpretation was done both in the strike and dip directions. Time and depth structure maps revealed reservoir closures to be anticlinal and fault supported in the field. Hydrocarbon volumes were calculated using the deterministic (map-based) approach. Stock tank oil initially in place (STOIIP) for the proven oil column estimated for the D-04 reservoir was 11.13 MMSTB, 0.54 MMSTB for D-06, and 2.16 MMSTB for E-09A reservoir. For the possible oil reserves, a STOIIP value of 7.28 MMSTB was estimated for D-06 and 6.30 MMSTB for E-09A reservoir, while a hydrocarbon initially in place (HIIP) of 4.13 MMSTB of oil equivalents was derived for the undefined fluid (oil/gas) in D-06 reservoir. A proven gas reserve of 1.07 MMSCF was derived for the D-06 reservoir. This study demonstrated the effectiveness of 3-D seismic and well logs data in delineating reservoir structural architecture and in estimating hydrocarbon volumes

CO2 storage algorithms involving the hybrid geological reservoir of the Irati Formation, Parana Basin

The injection and permanent storage of carbon dioxide (CO2) in depleted hydrocarbon reservoirs is a norm in atmospheric CO2 reduction practices. Currently, in the Irati Formation, there are no hydrocarbon production events; therefore, this study applies detailed petrophysical and seismic evaluations to present the algorithms for predicting CO2 storage potentials of the shale and carbonate reservoirs. There are studies involving the overview of the CO2 storage potential of the study location; however, an exhaustive presentation such as this is novel in the region. It proposes the shale-carbonate hybrid geological reservoir to maximise the storage capacity by reducing the geological constraints associated with thin-bedded layers, inadequate overburdens, water saturation (Sw), fault distributions, total organic content (TOC), and porosity (Ф). It reveals that the geological and other carbon capture and storage (CCS) related parameters presented for the conceived hybrid reservoir conform to the CO2 storage criteria considering the research results and existing atlases. The study shows average values for Ф (8.2% in shale and 13.1% in carbonates), TOC (8.8% in shale and 5.6% in carbonate) and reservoir thickness (13.7 m for shale and 15.4 m for carbonate) involving an estimated area of 4.3 × 109 m2. It presents an average value of 13.0% for Sw at depths ≥950 m, and the estimated CO2 storage capacity of the hybrid geological reservoir is 13.58 Gt. Therefore, the results of this study will assist in making an informed decision concerning the actualisation of CO2 storage within the Irati Formation and related geological units, especially in the absence of pre-determined data from hydrocarbon production.

Study on Nuclear Magnetic Resonance Logging T2 Spectrum Shape Correction of Sandstone Reservoirs in Oil-Based Mud Wells.

The oil-based mud filtrate will invade the formation under the overbalanced pressure during drilling operations. As a result, alterations will occur to the nuclear magnetic resonance (NMR) response characteristics of the original formation, causing the relaxation time of the NMR T2 spectrum of the free fluid part to move towards a slower relaxation time. Consequently, the subsequent interpretation and petrophysical evaluation will be heavily impacted. Therefore, the actual measured T2 spectrum needs to be corrected for invasion. For this reason, considering the low-porosity and low-permeability of sandstone gas formations in the East China Sea as the research object, a new method to correct the incorrect shape of the NMR logging T2 spectrum was proposed in three main steps. First, the differences in the morphology of the NMR logging T2 spectrum between oil-based mud wells and water-based mud wells in adjacent wells were analyzed based on the NMR relaxation mechanism. Second, rocks were divided into four categories according to the pore structure, and the NMR logging T2 spectrum was extracted using the multidimensional matrix method to establish the T2 spectrum of water-based mud wells and oil-based mud wells. Finally, the correctness of the method was verified by two T2 spectrum correction examples of oil-based mud wells in the study area. The results show that the corrected NMR T2 spectrum eliminates the influence of oil-based mud filtrate and improves the accuracy of NMR logging for calculating permeability.

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.

Exploration of Hidden Hydrocarbons in Old Wells Magid Field - Sirte Basin, Libya

Abstract: It is increasingly important to improve field productivity in today's competitive market. One way to achieve this, is to add new wells which are expensive and time consuming. The other alternative is to identify bypassed hydrocarbons, track changes in saturations and detect movement of reservoir fluid contacts from existing well bores already in place. It is considerably more cost effective and often more environmentally friendly to explore for those hidden hydrocarbons in old wells rather than drill new wells. As the field matures, there is a need to reevaluate the formation in older reservoirs and to focus the development strategy and approach on bypassed oil pockets and depletion levels in producing intervals. The ability to acquire essential logging data behind casing adds a new dimension to cased hole formation evaluation for locating and evaluating potential hydrocarbon zones in a mature field as in Magid field. A basic petrophysical evaluation was performed incorporating the data recorded behind casing by applying {Cased Hole Formation Resistivity Logging (CHFRL)} in each of these wells. Based on the analysis of cased hole formation evaluation results. The un-depleted intervals were commercially exploited adding reserve to the asset. Keywards: Hydrocarbon zones, Majid Field, Sirte Basin, Libya, CHFRL

Calibration of petrophysical evaluation results of clastic reservoirs using core data, in the offshore depobelt, Niger Delta, Nigeria

Calibration of petrophysical evaluation results of clastic reservoirs using core data, in the offshore depobelt, Niger Delta, Nigeria

Multi GPU parallelization of maximum likelihood expectation maximization method for digital rock tomography data

Digital rock is an emerging area of rock physics, which involves scanning reservoir rocks using X-ray micro computed tomography (XCT) scanners and using it for various petrophysical computations and evaluations. The acquired micro CT projections are used to reconstruct the X-ray attenuation maps of the rock. The image reconstruction problem can be solved by utilization of analytical (such as Feldkamp–Davis–Kress (FDK) algorithm) or iterative methods. Analytical schemes are typically computationally more efficient and hence preferred for large datasets such as digital rocks. Iterative schemes like maximum likelihood expectation maximization (MLEM) are known to generate accurate image representation over analytical scheme in limited data (and/or noisy) situations, however iterative schemes are computationally expensive. In this work, we have parallelized the forward and inverse operators used in the MLEM algorithm on multiple graphics processing units (multi-GPU) platforms. The multi-GPU implementation involves dividing the rock volumes and detector geometry into smaller modules (along with overlap regions). Each of the module was passed onto different GPU to enable computation of forward and inverse operations. We observed an acceleration of sim 30 times using our multi-GPU approach compared to the multi-core CPU implementation. Further multi-GPU based MLEM obtained superior reconstruction compared to traditional FDK algorithm.

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.

3D structural modeling integrated with seismic attribute and petrophysical evaluation for hydrocarbon prospecting at the Dhulian Oilfield, Pakistan

3D structural modeling integrated with seismic attribute and petrophysical evaluation for hydrocarbon prospecting at the Dhulian Oilfield, Pakistan

Petrophysical heterogeneity of the early Cretaceous Alamein dolomite reservoir from North Razzak oil field, Egypt integrating well logs, core measurements, and machine learning approach

Capturing the petrophysical heterogeneities within a reservoir has a critical influence on reservoir deliverability as well as field development programs. In this study, we report a comprehensive petrophysical evaluation of the oil-producing Aptian Alamein dolomite reservoir from the North Razzak field, Western Desert of Egypt. Integration of wireline logs and routine core analysis indicates that the Alamein reservoir has an extremely wide range of porosity (1–23%) and permeability (0.01–7000 mD), contributed by the early diagenetic dolomitization history and complex distribution of vugs. Petrophysical assessment by reservoir quality index (RQI) and flow zone indicator (FZI) infers that the megaporous rock types offer very good to excellent reservoir qualities and macroporosity dominated intervals are of fair to good quality. Further, we developed a permeability prediction model in this challenging carbonate rock based on Random Forest (RF) regression, and tested its efficacy and generalizability by well-defined performance metrics. The RF-based algorithm provided a more confident permeability prediction (R2 = 0.937) compared to conventional methods. Based on the petrophysical attributes; six distinct petrofacies (PF) associations are identified. PF-1, PF-3, and PF-5 provide excellent reservoir qualities with superlative storage capacity and hydraulic flow potential contributed by connected vugs, while the microporosity-dominated impervious PF-2 and PF-4 intervals act as intra-reservoir permeability barriers. We suggest that the higher initial oil production rate was mainly contributed by the larger connected pores and vuggy spaces. As reservoir pressure drops, hydrocarbon flows restrict to the smaller pores causing accelerated production weakening. Based on this comprehensive analysis, a suitable drilling and completion strategy is recommended for the future reservoir development program.

Petro-physical evaluation and identifying possible resource plays using the porosity and resistivity logs, Lower Indus Basin, Pakistan

Petro-physical evaluation and identifying possible resource plays using the porosity and resistivity logs, Lower Indus Basin, Pakistan

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.