An integrated sedimentological, rock typing, image logs, and artificial neural networks analysis for reservoir quality assessment of the heterogeneous fluvial-deltaic Messinian Abu Madi reservoirs, Salma field, onshore East Nile Delta, Egypt

El-Gendy, Nader; Radwan, Ahmed E.; Waziry, Mohamed A.; Dodd, Thomas J.H.; Barakat, Moataz Kh.

doi:10.1016/j.marpetgeo.2022.105910

Cited by 29 publications

(12 citation statements)

References 108 publications

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“…Many diagenetic processes, including micritization, dolomitization, cementation, neomorphism, dissolution, compaction (mechanical and chemical, i.e., stylolitization), and fracturing, have altered the Chorgali Formation . Diagenetic processes play an important role in altering the quality of the reservoir and affect the stratigraphic–structural play significantly. ,− In the case of the Chorgali Formation within the MOF, the diagenetic processes enhancing the reservoir quality include dolomitization, dissolution, and fracturing. However, micritization, cementation, neomorphism, and compaction played major roles in reducing the reservoir properties.…”

Section: Resultsmentioning

confidence: 99%

“… 55 Diagenetic processes play an important role in altering the quality of the reservoir and affect the stratigraphic–structural play significantly. 23 , 87 − 89 In the case of the Chorgali Formation within the MOF, the diagenetic processes enhancing the reservoir quality include dolomitization, dissolution, and fracturing. However, micritization, cementation, neomorphism, and compaction played major roles in reducing the reservoir properties.…”

Section: Resultsmentioning

confidence: 99%

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Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling

et al. 2022

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The Meyal oil field (MOF) is among the most important contributors to Pakistan's oil and gas industry. Northern Pakistan's Potwar Basin is located in the foreland and thrust bands of the Himalayan mountains. The current research aims to delineate the hydrocarbon potential, reservoir zone evaluation, and lithofacies identification through the utilization of seven conventional well logs (M-01, M-08, M-10, M-12, M-13P, and M-17). We employed the advanced unsupervised machine-learning method of selforganizing maps for lithofacies identification and the novel Quanti Elan model technique for comprehensive multimineral evaluation. The shale volume, porosity, permeability, and water saturation (petrophysical parameters) of six wells were evaluated to identify the reservoir potential and prospective reservoir zones. Well-logging data and self-organizing maps were used in this study to provide a less costly method for the objective and systematic identification of lithofacies. According to the SOM and Pickett plot analyses, the zone of interest is mostly made up of pure limestone oil zone, whereas the sandy and dolomitic behavior with a mixture of shale content shows non-reservoir oil−water and water zones. The reservoir has good porosity values that range from 0 to 18%, but there is a high water saturation of up to 45% in reservoir production zones. The presence of shale in the entire reservoir interval has a negative effect on the permeability value, but the petrophysical properties of the Meyal oil reservoir are good enough to permit hydrocarbon production. According to the petrophysical estimates, the Meyal oil field′s Sakesar and Chorgali Formations are promising reservoirs, and new prospects for drilling wells in the southern and central portions of the eastern portion of the research area are recommended.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling

et al. 2022

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“…Chlorite is attached to the surface of detrital particles in the form of films or combs and blocks pores and throats (Wang et al, 2019;Su et al, 2022). Thin-section analysis shows that sandstones with high content of plastic particles such as mica and mudstone debris are significantly affected by mechanical compaction, and their surface porosities are generally low (El-Gendy et al, 2022).…”

Section: Compaction and Pressure Solutionmentioning

confidence: 99%

Reservoir properties and hydrocarbon enrichment law of Chang 1 oil layer group in Yanchang Formation, Wanhua area, Ordos Basin

Xue²,

Sun³

et al. 2023

Front. Earth Sci.

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Evaluation of tight oil reservoir properties is of great significance to the exploration of oil and gas in tight reservoirs. The Chang 1 Member of the Yanchang Formation in the Wanhua Area, Ordos Basin is a new exploration stratum for tight sandstone oil. The lack of understanding of reservoir characteristics and crude oil enrichment rules has seriously restricted the efficient development of oil and gas resources in this stratum. In this study, the reservoir characteristics of the Chang 1 Member in the Wanhua area and the effects of superimposed sand bodies, structures and paleogeomorphology on accumulation of hydrocarbons were systematically studied. The Chang 1 sandstone is a typical ultra-low porosity-ultra-low permeability reservoir, and it has experienced destructive diagenesis of mechanical compaction, pressure solution and cementation, and constructive diagenesis of dissolution. Strong pressure solution caused the secondary enlargement of quartz and feldspar and the formation of patchy dense mosaic structures. The target layer has experienced argillaceous, siliceous and carbonate cementations. Moreover, the sandstone reservoir in the Chang 1 Member also experienced strong dissolution, and it is the main factor for the formation of secondary pores and the improvement of reservoir physical properties. The study also found that the main types of pores in the Chang 1 Member are intergranular dissolved pores and remaining intergranular pores. Superimposed sand bodies, nose-shaped uplifts, dominant facies and eroded paleo-highlands have significant effects on the hydrocarbon accumulation. Based on this study, it was found that the migration and accumulation mode of hydrocarbons in the Chang 1 reservoir belongs to the ladder-like climbing migration + structural ridge accumulation type. In addition, sand body thickness is an important controlling factor for the hydrocarbon accumulation. At present, the discovered crude oil in the Chang 1 Member is always distributed in the areas with thick sand bodies (>20 m), and most of the sand bodies have a thickness in the range of 25–40 m, and the effective thickness is in the range of 2–6 m. In addition, the eroded highlands are the highest topographic units, they are favorable areas for the large-scale accumulation of oil and gas.

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“…The components of a reservoir with harmonic lateral continuity in the geological characteristics that control fluid flow in reservoirs are known as HFUs (Abu‐Hashish et al, 2022; Amaefule et al, 1993; Rezaee et al, 2007). HFUs are based on the difference in petrophysical parameters, lithology and flow behaviour (El‐Gendy et al, 2022; Kochenov & Baturin, 2002). An FZI is calculated from the normalized porosity and the RQI (Abbaszadeh et al, 1996; Hearn et al, 1984).…”

Section: Introductionmentioning

confidence: 99%

“…HFUs are based on the difference in petrophysical parameters, lithology and flow behaviour (El-Gendy et al, 2022;Kochenov & Baturin, 2002).…”

Section: Introductionmentioning

confidence: 99%

Rock typing of the Miocene Hammam Faraun alluvial fan delta sandstone reservoir using well logs, nuclear magnetic resonance, artificial neural networks, and core analysis, Gulf of Suez, Egypt

Ahmed¹,

el‐Din

Radwan

et al. 2023

Geological Journal

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The application of integrated methods to evaluate the quality of reservoir rocks is becoming crucial in petroleum geoscience. The Miocene reservoirs in the El Morgan Oil Field consist mainly of sandstones with interbedded dolomitic silts and shales. Based on the pore scale, the sandstone reservoir of Hammam Faraun Member is a heterogeneous reservoir, and this is the main challenge in this oil field that affects both production and exploration activities. In this article, we have integrated the well logs, nuclear magnetic resonance (NMR), artificial neural networks (ANN) and core analysis to better understand these alluvial fan sandstone reservoirs. The petrographic description indicates arkosic sandstone with varied pore types, texture, cement, and sorting. The studied flow and storage capacity for well#1, indicate four rock types with 24 flow units and eleven barriers, which indicates a high degree of heterogeneity. The artificial neural networks (ANN), that is, the K.mod module, were used to enhance the prediction quality and forecast of FZI in the uncored intervals, where the NMR‐calculated permeability acts as a calibration point for the FZI model validation. This study reveals that the FZI is controlled by permeability, which is mostly influenced by pore throat size. The NMR log showed varied free fluid volume with varied capillaries, clay‐bound volumes and minor streaks of tar along the studied unit. The reservoir pores in the study area are residual pores that have undergone mechanical compaction and cementation that reduce porosities, while dissolution enhances the sandstone porosities. Porosity and permeability were significantly reduced in the presence of clays and carbonate minerals, which indicates poor reservoir quality zones in some parts. The primary factor influencing permeability is pore throat size, which is heavily influenced by the depositional environment and subsequent diagenetic processes. The findings of this study could lead to the development of accurate reservoir static models for future exploration and development plans in the studied area and elsewhere in similar depositional settings.

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An integrated sedimentological, rock typing, image logs, and artificial neural networks analysis for reservoir quality assessment of the heterogeneous fluvial-deltaic Messinian Abu Madi reservoirs, Salma field, onshore East Nile Delta, Egypt

Cited by 29 publications

References 108 publications

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling

Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling

Reservoir properties and hydrocarbon enrichment law of Chang 1 oil layer group in Yanchang Formation, Wanhua area, Ordos Basin

Rock typing of the Miocene Hammam Faraun alluvial fan delta sandstone reservoir using well logs, nuclear magnetic resonance, artificial neural networks, and core analysis, Gulf of Suez, Egypt

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