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Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to conduct a comprehensive formation evaluation of a pilot area within the Upper Shale Member of the Rumaila Oil Field. This evaluation is an essential step in the full development of the field. The application of well-log data and core analyses can help in obtaining the desired information about the geological characteristics of the formation. The process begins with measuring the formation temperature and water resistance utilizing Schlumberger’s charts and equations. The volume of shale was determined by two different methods, which were then used together to obtain the final shale volume. The porosity was determined using the conventional porosity equations from the porosity logs and the saturation was estimated based on Archie's equation. In core data analysis, an unconventional technique was utilized to determine rock type and permeability. The core porosity and the permeability were classified into four groups mainly using a self-organizing map and an unsupervised machine-learning method, and selected regression equations of each group were applied to estimate permeability in the core. The method depicted a good agreement between the core and estimated permeabilities, proving it as an effective tool. A complicated training data set was constructed based on the use of a multilayer perceptron neural network on coreless wells to identify rock types and permeability. Analyzing the petrophysical properties of the study area showed evidence that this area is characterized by heterogeneity. The heterogeneity of this formation is due to the presence of a considerable amount of shale, in addition to the significant characteristic differences in the layers and the same layer in different locations. The abundance of shale rock poses challenges during drilling operations, particularly due to shale washout which can lead to mechanical issues with the drilling string. Therefore, caution is advised when drilling new wells in the area to mitigate shale washout risks. Furthermore, the analysis identified layers with high hydrocarbon saturation that are viable for production. Conversely, some layers, characterized by shale presence and poor rock quality, are deemed unsuitable for production, and should not be considered as reservoir rock.

Abstract The key problem in oil exploration and engineering is the lack of accurate and reliable data about the reservoir parameters of a field. Having a precise assessment of petrophysical properties can provide the ability to make decisions with a high degree of confidence about planning for production, exploitation, and further field development scenario. In this research, an artificial intelligence (AI)-based approach was developed to improve the estimation of reservoir parameters including porosity and volume of shale, which has a significant role in different stages of hydrocarbon exploration, in the Kashafrud Gas Reservoir in the northeast of Iran. For this purpose, we measured the petrophysical properties of 27 samples of the Kashafrud Formation. To increase the amount of data for employing a multilayer perceptron (MLP) artificial neural network (ANN), a geostatistical algorithm was used to increase the amount of laboratory measured data of porosity and volume of shale to 686 and 702, respectively. In addition, 2263 well-logging data from the same well were provided. The optimal MLP network with the topology of 6-7-1, and 6-8-1 was selected to estimate the porosity and shale volume with mean squared error (MSE) of 2.78731E−4, and 1.28701E−9, respectively. The training process was performed using two different sets of input data. In the first approach, all available well-logging data were used as input, ending up in high MSE. In the second approach, some selected well logs were used based on the results of sensitivity analysis which clearly improved the estimations. The ability of MLP networks made great improvements in the estimation of the both parameters up to 99.9%. The presence of valuable core data in this study significantly improved the process of comparison and conclusion. The final results prove that AI is a trusted method, also the potential of the ANN method for the reservoir characterization and evaluation associated problems should be taken into consideration. Due to the unavailability of core data along the whole wells, the application of intelligent methods, such as machine learning (ML) can be used to estimate the parameters in other oil or gas fields and wells.

The key problem in oil exploration and engineering is the lack of accurate and reliable data about the reservoir parameters of a field. Having a precise assessment of petrophysical properties can provide the ability to make decisions with a high degree of confidence about planning for production, exploitation, and further field development scenario. In this research, an artificial intelligence (AI)-based approach was developed to improve the estimation of reservoir parameters including porosity and volume of shale, which has a significant role in different stages of hydrocarbon exploration, in the Kashafrud Gas Reservoir in the northeast of Iran. For this purpose, we measured the petrophysical properties of 27 samples of the Kashafrud Formation. To increase the amount of data for employing a multilayer perceptron (MLP) artificial neural network (ANN), a geostatistical algorithm was used to increase the amount of laboratory measured data of porosity and volume of shale to 686 and 702, respectively. In addition, 2263 well-logging data from the same well were provided. The optimal MLP network with the topology of 6-7-1, and 6-8-1 was selected to estimate the porosity and shale volume with mean squared error (MSE) of 2.78731E−4, and 1.28701E−9, respectively. The training process was performed using two different sets of input data. In the first approach, all available well-logging data were used as input, ending up in high MSE. In the second approach, some selected well logs were used based on the results of sensitivity analysis which clearly improved the estimations. The ability of MLP networks made great improvements in the estimation of the both parameters up to 99.9%. The presence of valuable core data in this study significantly improved the process of comparison and conclusion. The final results prove that AI is a trusted method, also the potential of the ANN method for the reservoir characterization and evaluation associated problems should be taken into consideration. Due to the unavailability of core data along the whole wells, the application of intelligent methods, such as machine learning (ML) can be used to estimate the parameters in other oil or gas fields and wells. [ABSTRACT FROM AUTHOR]

The Upper Triassic Kurra Chine Formation in the Sarta oil field of the Kurdistan Region of Northern Iraq has garnered limited attention, notwithstanding the keen interest of numerous international oil companies in drilling wells within this geological epoch. This study endeavors to thoroughly investigate the Formation Evaluation and petrophysical properties of the Kurra Chine Formation in the production oil field, with a specific focus on Sarta Well-2 (S-2). The research incorporates diverse methods for formation evaluation and analysis of petrophysical properties, employing conventional wireline logs such as Gamm-Ray, Neutron, Density, Sonic, Resistivity, Caliper, and Bit size.The research findings reveal that the thickness of the Kurra Chine Formation in S-2 is approximately 380 m. The pay zones of S-2 exhibit an average shale volume of 17 %. The dominant lithology in S-2 comprises Limestone, Dolomite, Anhydrite, Shale, and Sandstone. The average total porosity within the pay zones is determined to be 6 % in S-2. Furthermore, the average effective porosity in reservoir zones of the S-2 is estimated to be 5 %, while the average secondary porosity in these zones is found to be 6 % in S-2. The average permeability in the pay zones of the Sarta well is reported to be 30.6 millidarcy (mD). Additionally, the average water saturation in the pay zones is determined to be 35 % in S-2, whereas the average hydrocarbon saturation is estimated to be 45 % in S-2.This study furnishes comprehensive descriptions and analyses of the formation evaluation and petrophysical properties of the Kurra Chine Formation in Northern Iraq, shedding light on the characteristics and potential of this oil-bearing formation.

Unconventional reservoirs, including gas shales and tight gas sands, have gained prominence in the energy sector due to technological advancements and escalating energy demands. The oil industry is eagerly refining techniques to decipher these reservoirs, aiming to reduce data collection costs and uncertainties in reserve estimations. Characteristically, tight reservoirs exhibit low matrix porosity and ultra-low permeability, necessitating artificial stimulation for enhanced production. The efficacy of the stimulation hinges on the organic material distribution, the rock's mechanical attributes, and the prevailing stress field. Comprehensive petrophysical analysis, integrating standard and specialized logs, core analyses, and dynamic data, is pivotal for a nuanced understanding of these reservoirs. This ensures a reduction in prediction uncertainties, with parameters like shale volume, porosity, and permeability being vital. This article delves into an intricate petrophysical evaluation of the Nene field, a West African unconventional reservoir. It underscores the geological intricacies of the field, the pivotal role of data acquisition, and introduces avant-garde methodologies for depth matching, rock typing, and the estimation of permeability. This research highlights the significance of unconventional reservoir exploration in today's energy milieu, offering a granular understanding of the Nene field's geological challenges and proffering a blueprint for analogous future endeavours in unconventional reservoirs. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to better manage producing reservoirs and optimally place additional production wells, there is need to carry out a detailed hydrocarbon prospectivity studies in any given field. The aim of this paper was to integrate 3D seismic volume and wire-line logs from five wells with seismic attribute analysis in evaluating hydrocarbon prospects across the "Zech" field in the eastern part of the Coastal Swamp depo-belt of the Niger Delta Basin. Emphasis were on identification and correlation of reservoir intervals, formation evaluation, structural interpretation and mapping of reservoir tops, and amplitude extraction from seismic attribute analysis. Result from this prospect evaluation studies reveals that five reservoir zones (Z1, Z2, Z3, Z4 and Z5) were identified. Correlation of these reservoir zones across wells, shows that there were influence of structures on reservoir package, as variable thicknesses of zones were observed across faults. Petrophyiscal analysis of key reservoir properties shows that the reservoir of interest were characterized by average shale volume of 0.10 (10%), porosity of 0.23 v/v (23%) and permeability 1220 mD. In addition, the water saturations ranged between 0.08 and 0.39 v/v (8-39%), with corresponding hydrocarbon saturations that ranged from 0.60-0.91v/v (60-91%). These values indicate that the reservoirs properties were of good quality. Structural interpretation revealed the presence of growth faults and associated rollover anticline, collapsed crest structures, series of hanging walls and footwalls, which constitutes major hydrocarbon traps in the area. Generated structural top maps revealed that theses faults form structural closures. Extracted amplitude from seismic attribute analysis revealed the presence eight-hydrocarbon prospective zones that were amplitude supported. Generally, this integrated data and analytical approach is key in understanding reservoir evaluation and hydrocarbon prospectivity studies. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The saturation calculation in complex reservoirs remains a major challenge to the oil and gas industry. In simple formations, a tendency towards simple saturation models such as Archie or Simandoux for clean and shaly reservoirs respectively is always preferable. These models were found to be working effectively in homogeneous formations within which the porosity and permeability are linked in the light of a simple facies scheme. Where the rocks show some degrees of heterogeneity, the well-logs are usually affected by different factors. This adversely results in a compromised or averaged log profiles that may affect the saturation calculations. Four wells drilled across a shaly sand of high heterogeneity have been studied in the Perth Basin, Western Australia. The aim is to resolve the hydrocarbon saturation and explain the high productivity results, despite the high water saturation, obtained through a conducted formation well test across the interested reservoir zones. A new integration technique between a suite of conventional and advanced logging tools together with the capillary pressure measurements has been carried out to generate a high-resolution reservoir saturation profile, that is lithofacies dependent. Three different independent methods were used in the studied wells to calculate the saturation and to reduce the uncertainty of the final estimated profiles. The methods are the resistivity-based saturation, the NMR-based irreducible saturation, and a new application through saturation height modeling. Furthermore, through the workflow, an effective calibration for the magnetic resonance T2 cutoff has been applied that is supported by the excellent reservoir production behavior from such complex reservoir. The methodology will help resolve the saturation calculation as one of the most challenging reservoir parameters, particularly where the resistivity logs are affected in complicated shaly sand environments. The effectiveness of the workflow shines the possibility to predict high resolution facies and saturation profiles in the lack of resistivity logs. A further possibility can complete the analysis on real time basis, which can certainly provide facies and saturation profiles extended to the uncored wells. Application of this methodology in the uncored wells has shown very encouraging results in various well trajectories, either vertical, deviated or horizontal long boreholes.

The concept of geological engineering-integrated fracturing is widely applied in the conventional and unconventional reservoirs, aiming to achieve efficient and economic development. There is no doubt that fine reservoir evaluation is the basis and core of geological engineering-integrated fracturing. Therefore, in this paper, we performed a series of investigations on the basis of formation fine evaluation by using RoqScan technology. Firstly, the physical parameters of the target well located in Daniudi Gas Field were evaluated by a laboratory test and logging interpretation. Next, the composition and function of the RoqSCAN tool were introduce in detail. Furthermore, the elements, minerals, and rock mechanical parameters of the target well were evaluated by the RoqSCAN tool. Finally, the fine reservoir model was established on the basis of fine formation evaluation. Moreover, we conducted a series of research on porosity and principal stress of the target formation to compare the difference between the fine model and the conventional model. Based on the fine reservoir model, the acid-fracturing design and numerical simulation were further investigated. The results of experiments and numerical simulation mainly achieved the following findings: 1. The porosity and permeability of the target formation indicated that it was a tight, low-permeability reservoir; 2. According to the comparison of the distribution for different parameters in the target well, the modeling with fine reservoir evaluation had higher accuracy than the traditional modeling; 3. Based on the fine evaluation results, acid fracturing is recommended as a stimulation method to enhance the productivity of the target formation. This study provides an essential method for the integrated fracturing design of geological engineering. [ABSTRACT FROM AUTHOR]

Purpose. The research is aimed at evaluating the petrophysical characteristics of the Late Cretaceous Matulla Formation in the central part of the Gulf of Suez in order to detect its hydrocarbon reservoir potential. Methods. Well logs from five wells (Muzhil-1, -2, -4, -7, -8) were used to evaluate the Matulla reservoirs based on a computerized approach. Petrophysical parameters and fluid types were calculated, verified using core data, and represented vertically as lithosaturation cross plots and laterally as isoparametric variation maps. Findings. Evaluation of total porosity (Ft), effective porosity (Fe), shale content (Vsh), water saturation (Sw), permeability (K), bulk volume of water (BVW), and net pay characteristics of Matulla Formation in the Muzhil wells showed the following weighted average values: 18-23%, 15-19%, 21-40%, 20-100%, 1.1-281 mD, 3-21% and 0-83 ft, respectively. The Log-derived lithology identification indicates that the major matrix component of the Matulla Formation is quartzose sandstone with minor shale and carbonate contents. The upper zone is a poor reservoir, while the middle and lower zones are considered good reservoirs in all studied wells. It is expected that Muzhil-2 will produce oil without water; however, Muzhil-1 and Muzhil-4 will produce oil with water; while Muzhil-7 and Muzhil-8 will produce water only. Originality. Detailed log-derived petrophysical evaluation, verified by core analysis and well tests (DST and MDT), construction of lithosaturation cross plots for each well and isoparametric petrophysical maps are performed for the first time for Matulla Formation in the Muzhil field. Practical implications. The obtained results on lithosaturation and petrophysics have expanded the knowledge about the characteristics of the Matulla Formation sediments, hosting promising reservoir intervals, and should be taken into account in future exploration and development of the Muzhil field. [ABSTRACT FROM AUTHOR]

Formation evaluation in thin bed lamination is challenging and classic petrophysical workflow would results in underestimation of true hydrocarbon pore thickness and consequently underestimation of hydrocarbon in place in oil and gas fields. Due to deficiency of conventional well logs to detect thin bed shale sand laminations, they appear as non- hydrocarbon bearing low resistivity interval on well logs. True log response cannot be recorded in thin bed shale sand lamination intervals since thickness of these layers is lower than logging tool resolution. Logging tools can only record the average log response of shale and sand together – rather than true response of sand - anywhere the thickness of each lamination falls below vertical resolution of logging tools. Forward modeling and inversion workflow was applied in a thinly laminated shaly sand reservoir to calculate true hydrocarbon pore thickness. The process of forward modeling and inversion was optimized by using Genetic Algorithm approach by developing a computer code. A new workflow for formation evaluation was proposed for formation evaluation in thin bed shale sand laminations and verified successfully. The result was fully integrated and verified with core, well log and production data. True hydrocarbon pore thickness was increased, and new perforation interval was suggested based on the findings.

The re-evaluation of oil-bearing wells enables finding potential oil-bearing areas and estimating the results of well logging. The re-evaluation of oil bearing is one of the key procedures for guiding the development of lower production wells with long-term production histories. However, there are many limitations to traditional oil-bearing assessment due to low resolution and excessive reliance on geological expert experience, which may lead to inaccurate and uncertain predictions. Based on information gain, three data-driven models were established in this paper to re-evaluate the oil bearing of long-term production wells. The results indicated that the RF model performed best with an accuracy of 95.07%, while the prediction capability of the neural network model was the worst, with only 79.8% accuracy. Moreover, an integrated model was explored to improve model accuracy. Compared with the neural network, support vector machine, and random forest models, the accuracy of the fusion model was improved by 20.9%, 8.5%, and 1.4%, which indicated that the integrated model assisted in enhancing the accuracy of oil-bearing prediction. Combined with the long-term production characteristics of oil wells in the actual oil field, the potential target sweet spot was found, providing theoretical guidance for the effective development of lower production wells in the late period of oilfield development. [ABSTRACT FROM AUTHOR]

Unconventional reservoirs, including gas shales and tight gas sands, have gained prominence in the energy sector due to technological advancements and escalating energy demands. The oil industry is eagerly refining techniques to decipher these reservoirs, aiming to reduce data collection costs and uncertainties in reserve estimations. Characteristically, tight reservoirs exhibit low matrix porosity and ultra-low permeability, necessitating artificial stimulation for enhanced production. The efficacy of the stimulation hinges on the organic material distribution, the rock’s mechanical attributes, and the prevailing stress field. Comprehensive petrophysical analysis, integrating standard and specialized logs, core analyses, and dynamic data, is pivotal for a nuanced understanding of these reservoirs. This ensures a reduction in prediction uncertainties, with parameters like shale volume, porosity, and permeability being vital. This article delves into an intricate petrophysical evaluation of the Nene field, a West African unconventional reservoir. It underscores the geological intricacies of the field, the pivotal role of data acquisition, and introduces avant-garde methodologies for depth matching, rock typing, and the estimation of permeability. This research highlights the significance of unconventional reservoir exploration in today’s energy milieu, offering a granular understanding of the Nene field’s geological challenges and proffering a blueprint for analogous future endeavours in unconventional reservoirs.

The current utility of mud gas data is typically limited to geological and petrophysical correlation, formation evaluation, and fluid typing. A critical and comprehensive review of the literature on mud gas data revealed that the mud gas data is abundantly acquired during drilling but not sufficiently utilized in real time. There is the need to leverage the current advances in machine learning technology and the race towards the digital transformation of the petroleum industry to create new opportunities for more extensive utility of mud gas data. Now that data is the new “oil” or “gold”, the utility of the rich and abundant mud gas data could be explored for real-time applications. Such new possibilities are capable of adding more value to the reservoir characterization workflow ahead of geophysical logging, geological core data analysis, and well testing. Achieving this will facilitate early decision-making, improve safety, reduce nonproductive time, and ultimately accelerate the attainment of the digital transformation objective of the petroleum industry. We conclude with identifying possible future directions for the ultimate attainment of maximizing the utility of mud gas data through real-time and more advanced applications.

Copyright of Geologia USP: Série Científica is the property of Geologia USP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sequence stratigraphy and Electrosequence of the Don-Field Central Swamp depobelt of the Niger Delta Basin, was carried out using well logs, biostratigraphic and core data. The aim of this study is to re-characterise and revalidate the reservoirs within the study area and provide an optimum framework for predicting reservoir character, development and reservoir quality distribution. Detailed petrophysical evaluation reveals proficient hydrocarbon reservoir units with variable parameters (i.e. porosity, permeability and shale volume) that can accommodate productive hydrocarbon reserve. Core data analyses revealed heavy minerals like pyrites and glauconites that can be of economic interest. The gamma wireline signatures of the wells show reservoir units that are predominantly blocky in shape indicative of fluvial channels. Fluvial channels are typically associated with coastal and/or marginal marine environments. More so, the aforementioned observations were validated using palaeoenvironmental interpretation of strata penetrated by Well-1, Well-2, and Well-3 via the sidewall core analyses. Sequence stratigraphic surfaces such as maximum flooding surfaces (MFS) and sequence boundary (SB) were observed to show good correlation with palynological and foraminiferal zones. The stacking patterns (i.e. progradation, retrogradation and aggradation) encountered gave acumen into systems tracts (i.e. lowstand system tract (LST), transgressıve system tract (TST) and highstand system tract (HST) interpretation. These system tracts constitute a depositional sequence set of middle—late Miocene age bounded chronologically by MFS of 9.5 Ma, 12.8 Ma, 15.0 Ma, 15.9 Ma and SB of 12.1 Ma, 13.1 Ma, 15.5 Ma, 15.9 Ma. The SB and MFS were delineated based on Shell Petroleum Development Company (SPDC) biozonation scheme: F-zone and P-zone were within P820-P680 and F9500-F9600/F9700 as contained in the biofacies interpreted data of index fossils (Globorotalia foshi S.I; Globorotalia praefohsi; Globorotalia peripheroacuta; Orbulina spp; Praeorbulina sicana; Paragloborotalia mayeri; Neogloboquadrina acostaensis) which corresponded to the alphanumeric code N8–N16 planktonic foraminiferal zones of Blow. [ABSTRACT FROM AUTHOR]

This paper aims to establish a complete workflow for a petrophysical evaluation to enhance and quantify hydrocarbon prospect and productivity of Shahd SE field, East Ras Qattara concession, Western desert, Egypt. The suggested workflow can, then, be used with the same steps and sequences for any petrophysical evaluation study. Well logs data from four wells were used for this study. The present data has drilled through three formations: (1) Bahariya Formation, which has been divided into two subzones; (I) Upper Bahariya, a shaly formation and (II) Lower Bahariya, the main reservoir present in our case study. (2) Kharita Formation, which consist of clean sand. We will evaluate the three most useful petrophysical parameters: (a) volume of shale (Vsh) using the gamma-ray (GR), (b) effective porosity (Φeff) using the neutron log and the resulting volume of shale as an input, and (c) water saturation (Sw). Several equations were used to calculate the Sw. The best equation was Simandoux equation to put in consideration the shale model of the upper Bahariya. The results show that the net reservoir and net pay thicknesses were seen very promising in all four wells, all at the lower Bahariya Formation. The reservoir quality parameters “Effective Porosity (Φeff)” were almost the same for all four wells, as well as the high hydrocarbon saturation “Sh” for all four wells. [ABSTRACT FROM AUTHOR]

Drilling deviated wells has become customary in recent times. This work condenses various highly deviated and horizontal well log interpretation techniques supported by field examples. Compared to that in vertical wells, log interpretation in highly deviated wells is complex because the readings are affected not only by the host bed but also the adjacent beds and additional wellbore-related issues. However, understanding the potential pitfalls and combining information from multiple logs can address some of the challenges. For example, a non-azimuthally focused gamma ray logging while drilling (LWD) tool, used in combination with azimuthally focused density and neutron porosity tools, can accurately tell if an adjacent approaching bed is overlying or underlying. Moreover, resistivity logs in horizontal wells are effective in detecting the presence of adjacent beds. Although the horns associated with resistivity measurements in highly deviated wells are unwanted, their sizes can provide important clues about the angle of the borehole with respect to the intersecting beds. Inversion of horizontal/deviated well logs can also help determine true formation resistivities. Additionally, observed disagreement between resistivity readings with nuclear magnetic resonance (NMR) T2 hydrocarbon peaks can indicate the presence or absence of hydrocarbons. Furthermore, variations in pulsed neutron capture cross sections along horizontal wells, measured while injecting various fluids, can indicate high porosity/permeability unperforated productive zones. Finally, great advances have been made in the direction of the bed geometry determination and geologic modeling using the mentioned deviated well logs. More attention is required toward quantitative log interpretation in horizontal/high angle wells for determining the amount of hydrocarbons in place. [ABSTRACT FROM AUTHOR]

The main goal of this study is to evaluate Mishrif Reservoir in Abu Amood oil field, southern Iraq, using the available well logs. The sets of logs were acquired for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5. The evaluation included the identification of the reservoir units and the calculation of their petrophysical properties using the Techlog software. Total porosity was calculated using the neutron-density method and the values were corrected from the volume of shale in order to calculate the effective porosity. Computer processed interpretation (CPI) was accomplished for the five wells. The results show that Mishrif Formation in Abu Amood field consists of three reservoir units with various percentages of hydrocarbons that were concentrated in all of the three units, but in different wells. All of the units have high porosity, especially unit two, although it is saturated with water. [ABSTRACT FROM AUTHOR]

The re-evaluation of oil-bearing wells enables finding potential oil-bearing areas and estimating the results of well logging. The re-evaluation of oil bearing is one of the key procedures for guiding the development of lower production wells with long-term production histories. However, there are many limitations to traditional oil-bearing assessment due to low resolution and excessive reliance on geological expert experience, which may lead to inaccurate and uncertain predictions. Based on information gain, three data-driven models were established in this paper to re-evaluate the oil bearing of long-term production wells. The results indicated that the RF model performed best with an accuracy of 95.07%, while the prediction capability of the neural network model was the worst, with only 79.8% accuracy. Moreover, an integrated model was explored to improve model accuracy. Compared with the neural network, support vector machine, and random forest models, the accuracy of the fusion model was improved by 20.9%, 8.5%, and 1.4%, which indicated that the integrated model assisted in enhancing the accuracy of oil-bearing prediction. Combined with the long-term production characteristics of oil wells in the actual oil field, the potential target sweet spot was found, providing theoretical guidance for the effective development of lower production wells in the late period of oilfield development.

Copyright of Journal of Petroleum Research & Studies is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Bahariya Formation (Upper Cretaceous) hosts the most prospective hydrocarbon reservoirs in the Western Desert, Egypt. The reservoir intervals consist mainly of fluvial and coastal marine sandstones, respectively, in the lower and upper Bahariya Formation. The definition of the best reservoir facies and the extent of reservoir heterogeneity are not very well constrained. This study presents a high-resolution definition for the reservoir facies distribution and heterogeneity in Salam Oil Field, north Western Desert. Seismic, well logs, and core analyses have been integrated in order to identify and categorize the different reservoir intervals. Detailed petrophysical well log and core studies have been utilized to further enhance our understanding of the magnitude of heterogeneity within the Bahariya sediments and therefore aid in constructing predictive models, which describe the fluid flow efficiency and reservoir performance. Four petrophysical rock types (PRT) have been identified; PRTI and PRT2 host the optimum reservoir properties and comprises the braided fluvial quartzose sandstones of the lower Bahariya (Av. phi = 20.74%, Av. KH = 367.53 mD, KV = 176.73 mD) with abundant megapores and isotropic, well-connected pore system. The upper Bahariya sediments only constitute the clay-and carbonate-rich PRT3 and PRT4 sediments that are dominated by micropores with predominant mesopores and a heterogeneous, poorly connected pore system. Upper Bahariya sediments have anisotropic pore-system (Av. permeability anisotropy > 3), reflecting the dominant anisotropic pore system. Eight hydraulic flow units (HFU) were identified; the reservoir efficiency decreases from HFU1 to HFU8. At megascale, the main flow conduits (speed zones) are predominantly composed of braided fluvial channel sandstones that mostly contain HFU1 and HFU2. The barrier zones are often associated with HFU7 and HFU8 and are commonly correlated with the lower Bahariya floodplain sediments and tidal flat, mixed tidal flat sediments of upper Bahariya. Notably, the greatest thickness of the upper Bahariya is classified as fluid flow baffles containing HFU5 and HFU6 with abundant micropores with good storage but low flow capacity. [ABSTRACT FROM AUTHOR]

The Lower Indus Basin in Pakistan has its significance and has proven oil and gas potential in Pakistan. To explore its hidden realities on basis of advance technologies of exploration geophysics, the present study has carried out to open new horizons in the field of exploration geophysics. It combines study of stratigraphical and structural trends of Lower Indus basin for each formation on regional scales including evaluation of resource potential based on seismic and well log data. The seismic interpretation models are based on iso velocity depth contour method and seismic inversion models are based on sparse spike models. The seismic inversion data approach was used first time on Indus basin to understand trapping mechanism of hydrocarbons with performing reservoir characterization. Tomography imaging has reveal earth properties and the focal mechanism inversion covered the geological formations. The data integration techniques such as co-kriging or neural networks were used for single and multiobjective function optimization for formations evaluation of entire area. The seismic amplitude and inversion anomaly, potentially indicative of porous reservoirs, are located in each formation. The results of cretaceous sand's reserve for lower Indus basin prove compressionional tectonics with many anticlinal and faults. The study is an important support for prospect evaluation and hydrocarbon reserve estimations and was necessary to delineate unexplored parts. [ABSTRACT FROM AUTHOR]

This paper shows the availability of using the Bayesian classification method to predict class membership probabilities in one of the deep tight reservoirs in Western Desert, Egypt. The workflow of our project that using the Bayesian method used the deterministic petrophysical results of three training wells to train the data and extract the classifiers. The classified data were modeled using Gaussian distribution for each lithofacies. The used wells were acquired from a deep Jurassic gas reservoir in the Western Desert of Egypt. The fitting between actual and modeled data has been reached by minimizing the L2 norm. Besides, a cross-validation process was used for validating the resulted classifiers. Finally, the Bayesian classification method can predict the GWC with an accuracy of 4 m. To avoid probability interference caused by the compacted shale more data should be added to the initial model. [ABSTRACT FROM AUTHOR]

Upper Safa Member is part of Jurassic Khatatba Formation; it consists of low net gross ratio sand streaks. The core and well logging data were used to perform a comprehensive reservoir evaluation. The Schlumberger application "Techlog" was used to perform the required evaluation analysis. Four oriented wells were selected for this study. The volume of shale "Vsh" using gamma-ray (GR) was used to evaluate the lithology and to discriminate sand "reservoir" from shale "non-reservoir". A porosity model using the density log was constructed and used as an input to calculate Archie's water saturation "Sw". Porosity- Permeability (Poro-Perm) Transform was used to evaluate the reservoir permeability. The net reservoir and net pay thicknesses were seen attractive in three out of four wells. The reservoir quality parameters "Porosity and Permeability" were different from well to well. The hydrocarbon saturation "Sh" was high in the three wells. The hydrocarbon intervals depths were highlighted and considered in the perforation strategy. [ABSTRACT FROM AUTHOR]

Statistical analysis methods have been widely used in all industries. In well logs analyses, they have been used from the very beginning to predict petrophysical parameters such as permeability and porosity or to generate synthetic curves such as density or sonic logs. Initially, logs were generated as simple functions of other measurements. Then, as a result of the popularisation of algorithms such as the k-nearest neighbours (k-NN) or artificial neural networks (ANN), logs were created based on other logs. In this study, various industry and general scientific programmes were used for statistical data analysis, treating the well logs data as individual data sets, obtaining very convergent results. The methods developed for processing well logs data, such as Multi-Resolution Graph-Based Clustering (MRGBC), as well as algorithms commonly used in statistical analysis such as Kohonen self-organising maps (SOM), k-NN, and ANN were applied. The use of the aforementioned statis-tical methods allows for the electrofacies determination and prediction of an Rt log based on the other recorded well logs. Correct determination of Rt in resistivity measurements made with the Dual Laterolog tool in the conditions of the Groningen effect is often problematic. The applied calculation methods allow for the correct estimation of Rt in the tested well.

The Upper Triassic Kurra Chine Formation in the Sarta oil field of the Kurdistan Region of Northern Iraq has garnered limited attention, notwithstanding the keen interest of numerous international oil companies in drilling wells within this geological epoch. This study endeavors to thoroughly investigate the Formation Evaluation and petrophysical properties of the Kurra Chine Formation in the production oil field, with a specific focus on Sarta Well-2 (S-2). The research incorporates diverse methods for formation evaluation and analysis of petrophysical properties, employing conventional wireline logs such as Gamm-Ray, Neutron, Density, Sonic, Resistivity, Caliper, and Bit size. The research findings reveal that the thickness of the Kurra Chine Formation in S-2 is approximately 380 m. The pay zones of S-2 exhibit an average shale volume of 17 %. The dominant lithology in S-2 comprises Limestone, Dolomite, Anhydrite, Shale, and Sandstone. The average total porosity within the pay zones is determined to be 6 % in S-2. Furthermore, the average effective porosity in reservoir zones of the S-2 is estimated to be 5 %, while the average secondary porosity in these zones is found to be 6 % in S-2. The average permeability in the pay zones of the Sarta well is reported to be 30.6 millidarcy (mD). Additionally, the average water saturation in the pay zones is determined to be 35 % in S-2, whereas the average hydrocarbon saturation is estimated to be 45 % in S-2. This study furnishes comprehensive descriptions and analyses of the formation evaluation and petrophysical properties of the Kurra Chine Formation in Northern Iraq, shedding light on the characteristics and potential of this oil-bearing formation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

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Abstract Low-field Nuclear Magnetic Resonance (NMR) is a non-invasive method widely used in the petroleum industry for the evaluation of reservoirs. Pore structure and fluid properties can be evaluated from transverse relaxation (T 2) distributions, obtained by inverting the raw NMR signal measured at subsurface conditions or in the laboratory. This paper aims to cast some light into the best practices for the T 2 data acquisition and inversion in shales, with a focus on the suitability of different inversion methods. For this purpose, the sensitivity to various signal acquisition parameters was evaluated from T 2 experiments using a real shale core plug. Then, four of the most common inversion methods were tested on synthetic T 2 decays, simulating components often associated with shales, and their performance was evaluated. These inversion algorithms were finally applied to real T 2 data from laboratory NMR measurements in brine-saturated shale samples. Methods using a unique regularization parameter were found to produce solutions with a good balance between the level of misfit and bias, but could not resolve adjacent fast T 2 components. In contrast, methods applying variable regularization – based on the noise level of the data – returned T 2 distributions with better accuracy at short times, in exchange of larger bias in the overall solution. When it comes to reproducing individual T 2 components characteristic of shales, the Butler-Reeds-Dawson (BRD) algorithm was found to have the best performance. In addition, our findings suggest that threshold T 2 cut-offs may be derived analytically, upon visual inspection of the T 2 distributions obtained by two different NMR inversion methods. Highlights • Short echo spacings (TE) can improve signal quality but also enhance early experimental noise. • Inversion methods using fixed smoothing cannot resolve adjacent T 2 components correctly. • Inversion methods based on noise level produce better fits but may bias solutions. • The BRD algorithm can differentiate the contribution from adjacent peaks at short T 2 times. • Threshold T 2 cut-offs are determined analytically by using two different NMR inversion methods. [ABSTRACT FROM AUTHOR]

Abstract The study area is located between latitudes 28° 4′ 12″ to 28° 4′ 50″ N and longitudes 33° 35′ 12″ to 33° 35′ 34″ E mainly in the Amal Field, the offshore southern Gulf of Suez basin. Kareem Formation which is subdivided into Shagar and Markha members is the object of study through integrating the subsurface geologic studies, well log evaluation and the petrophysical laboratory measurements in order to better understand hydrocarbon potentialities of Kareem Formation in Amal Field, using ten wells (Amal-5, Amal-9, Amal-10AST, Amal-11, Amal-12, Amal-13ST, Amal-15ST, Amal-17ST, Amal-18, and Amal-19) different types of open hole well logs for petrophysical parameters (shale content, porosity and fluid saturation) determination. Also the porosities were determined by using the available sonic, density and neutron logs. Four wells (Amal-15 ST, Amal-17 ST, Amal-18 and Amal-19) have been selected for evaluating the pore pressure for Kareem Formation based on corrected drilling exponent (Dxc) calculation, flow line temperature data, background gases, mud density, hole configuration data and wireline logs. A matching was observed between pore pressure values and hydrocarbon saturation in the studied area. [ABSTRACT FROM AUTHOR]

The daunting challenge in the exploration and production of oil and gas in the face of continual rise in the world's energy consumption has long been how to economically recover bypassed reserves within existing assets. This research is focused on the analysis of prospects and volumetric estimation of the hydrocarbon reservoirs delineated within an exploratory field using 3D seismic data and suites of wireline logs. The prospectivity of the delineated reservoir was carried out using seismo-structural interpretation and formation evaluation towards the assessment of the prolific hydrocarbon occurrence within the field. The reservoirs have porosity (0.29-0.32) for H1, (0.20-0.31) for H2 and (0.30-0.40) for H3 and the average computed hydrocarbon saturation of (0.31-0.62) for H1, (0.16-0.52) for H2 and (0.64-0.73) for H3, hydrocarbon pore volume (HCPV) of 28,706.95, 33,081.2 and 45,731.49 barrels for H1, H2 and H3, respectively, while the estimated stock tank oil initially-in-place (STOIIP) range (136.8-140.73) MMSTB for H1, (36.77-489.64) MMSTB for H2 and (166.62-308.14) MMSTB for H3. The observed porosity and hydrocarbon saturation for the delineated reservoirs as well as the estimated hydrocarbon pore volume and storage total oil in place indicate that the reservoirs are highly prolific. The study has therefore contributed to the understanding of hydrocarbon resource potential within the study area. [ABSTRACT FROM AUTHOR]

The southern periphery of the Abu-Gharadig basin in the Northern Egyptian Western Desert is characterized by some subsurface geological challenges related to the carbonate reservoir's quality, which requires precise petrophysical evaluation and seismic structural interpretation. Therefore, we conducted a subsurface mapping and formation evaluation for the Upper Cretaceous carbonate reservoirs in the Southwest Abu Sennan (SWS) area utilizing seismic reflection profiles and borehole geophysical data. Seismic mapping of the Upper Cretaceous carbonate reservoirs (Abu Roash (AR)/B,/D, and/F) revealed 3-way folds with NE-SW trends divided by NW-SE normal fault trends presenting significant chances for exploration. These closures were filled by hydrocarbons generated from the Jurassic source rocks. Formation evaluation was performed using the new petrophysical tool "Gaialog" which was coded using Python. Petrophysical parameters for the recognized net pay intervals of AR/B, AR/D, and AR/F carbonate reservoirs showed that the effective porosity (φ eff: Phie) and the hydrocarbon saturation (S h) increases towards the East to Southeast direction while the water saturation (S w) increases to the Northwest of the study area. The highest net pay and the effective porosity were found in the Eastern part of the study area. The study procedures can be applied in neighboring areas to evaluate and understand similar reservoirs. • Petrophysical analysis using a new tool created by Python (Gaialog) is applied. • Upper Cretaceous carbonate reservoirs is NE-SW folded and faulted by NW-SE segments. • Abu Roash/F Member has potential as an unconventional reservoir in Abu Gharadig basin. • Borehole imaging is crucial for carbonate reservoirs evaluation. • Automation in formation evaluation help with accuracy and time-saving. [ABSTRACT FROM AUTHOR]