Oil generation and expulsion modeling of the syn-rift Salif oil-source rock in the Tihamah Basin, Yemeni Red Sea: Implications for shale oil exploration

Hakimi, Mohammed Hail; Lashin, Aref; Varfolomeev, Mikhail A.; Rahim, Abdul; Sen, Souvik; Naseem, Waqas; Saeed, Shadi A.; Al‐Muntaser, Ameen A.; Qadri, S. M. Talha; Mustapha, Khairul Azlan

doi:10.1016/j.jafrearsci.2023.104924

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…The quality of source rocks can be determined by the type of TOC present [37]. The lab technique used for estimating TOC is called vitrinite reflection, where a rock sample is crushed and examined, but this requires the core sample of the rock and is then integrated with the subsurface model [47,48]. The correlation of logs makes it easy-to-get a general estimation of rock properties and helps in initial modeling, such as using a density log reciprocal model for TOC estimation [14].…”

Section: Porosity Estimationmentioning

confidence: 99%

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Ehsan,

Zaheer,

Abbasi

2024

Journal of GeoEnergy

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An approach is proposed to improve modeling for shale gas reservoirs, integrating key parameters such as total organic carbon (TOC) and porosity. Seismic inversion uses seismic reflection data and well-log information to improve geological and geophysical interpretation and estimate rock properties with high-resolution subsurface acoustic impedance, including low and high frequencies. The Ranikot Formation in the Central Indus Basin, Pakistan, is a Paleocene-age formation with the potential to act as reservoir, seal, and source rock. The porosity of the Lower Ranikot reservoir in the Mehar Block was calculated using seismic inversion analysis with the Mehar-02 well. The petrophysical analysis yielded an effective porosity of 5.8%. Similarly, when calculated using seismic inversion, the porosity fell within the 5.5%–6.0% range. Determining the TOC content is crucial in evaluating unconventional shale resources. Petrophysical approaches, such as the ΔlogR method, offer a fast, convenient, and cost-effective means of estimating TOC from well logs. This method is commonly used in conventional source rock evaluation and applied to unconventional resource play evaluation. On the other hand, seismic inversion techniques were used to conduct TOC analysis in the absence of core data in order to estimate the source potential of the Upper Ranikot Formation. To estimate the TOC log for the Upper Ranikot shales in the Mehar Block, the Passey equation was used on the well logs of the Mehar-02 well. The estimated TOC for the Upper Ranikot shales is around 2.0%, which falls within the fair TOC range.

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Section: Porosity Estimationmentioning

confidence: 99%

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Ehsan,

Zaheer,

Abbasi

2024

Journal of GeoEnergy

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Geochemical evaluation and source rock zonation by multi-layer perceptron neural network technique: a case study for Pabdeh and Gurpi Formations-North Dezful Embayment (SW Iran)

Jamshidipour,

Khanehbad,

Mirshahani

et al. 2023

J Petrol Explor Prod Technol

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In this study, using a multi-layer perceptron neural network (MLPNN) model, total organic carbon (TOC) and hydrogen index (HI) values for Pabdeh and Gurpi Formations in the oil fields of Naft Sefid (NS-13), Kupal (KL-36, KL-38, and KL-48) and Palangan (PL-2) were calculated in the North Dezful Embayment located in the southwest of Iran. To build the MLPNN model, the geochemical data calculated by the Rock–Eval pyrolysis method (TOC and HI) and the conventional petrophysical well log data, including sonic transit time log (DT), formation density log (RHOB), total resistivity log (RT), spectral gamma-ray log, computed gamma-ray log and neutron porosity log from the NS-13 well were used. The log data were the input layer, and the geochemical data were the output layer of the model. Twenty-four datasets were used for MLPNN training, and seven datasets were used for MLPNN testing. Two hidden layers were considered in this technique. Each hidden layer has an activation function (tanh) and a solver parameter (lbfgs). The accuracy of measurement of TOC and HI indices of Pabdeh and Gurpi Formations in terms of R2 was 0.93 and 0.90, respectively. This model has higher accuracy than the ΔlogR technique (R2: 0.28). Considering the relationships between the input data and other wireline logs is an advantage of this technique. These two formations have five source rock zones. Pabdeh Formation has three zones. The middle zone of the Pabdeh Formation (Pz. II) has the highest TOC (2.6 wt%) and source rock potential. Pabdeh Formation has kerogen type II. Gurpi Formation has a weaker source rock potential than Pabdeh Formation due to its low TOC content (< 1%). Both source rock zones of this formation have low TOC, but in some layers of the lower zone of the Gurpi Formation (Gz. II), high values for TOC were predicted. Gurpi Formation has Kerogen types II and III.

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Evaluation of facies heterogeneity in reef carbonate reservoirs: A case study from the oil field, Perm Krai, Central-Eastern Russia

Martyushev

Chalova

Davoodi

et al. 2023

Geoenergy Science and Engineering

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Oil generation and expulsion modeling of the syn-rift Salif oil-source rock in the Tihamah Basin, Yemeni Red Sea: Implications for shale oil exploration

Cited by 3 publications

References 29 publications

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Geochemical evaluation and source rock zonation by multi-layer perceptron neural network technique: a case study for Pabdeh and Gurpi Formations-North Dezful Embayment (SW Iran)

Evaluation of facies heterogeneity in reef carbonate reservoirs: A case study from the oil field, Perm Krai, Central-Eastern Russia

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