Facies modeling of synchronous successions - A case study from the mid-cretaceous of NW Zagros, Iran

Shoghi, Jaber; Bahramizadeh-Sajjadi, Hassan; Nickandish, A. A.; Abbasi, Madjid

doi:10.1016/j.jafrearsci.2019.103696

Cited by 21 publications

(9 citation statements)

References 24 publications

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“…Independently, an optimal number of clusters is computed based on the KRI. Eventually, the terminal clusters are constructed by merging the small clusters 1,5,6,9,18,26,34,42 .…”

Section: 2mrgc Clustering Methodsmentioning

confidence: 99%

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods

Eftekhari,

Memariani,

Maleki

et al. 2023

Preprint

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Electrofacies analysis conducted the distribution effects throughout the reservoir despite the difficulty of characterizing stratigraphic relationships. Clustering methods quantitatively define the reservoir zone from non-reservoir considering electrofacies. Asmari Formation is the most significant reservoir of the Mansouri oilfield in SW Iran, generally composed of carbonate and sandstone layers. The stratigraphical study is determined by employing 250 core samples from one exploratory well in the studied field. Five zones with the best reservoir quality in zones 3 and 5 containing sandstone/shale are determined. Moreover, multi-resolution graph-based and artificial neural network clustering involving six logs are employed. Utilizing Geolog software, an optimal model with eight clusters with better rock separation is obtained. Eventually, five electrofacies with different lithological compositions and reservoir conditions are identified and based on lithofacies describing thin sections, sandstone, and shale in zones 3 and 5 show high reservoir quality. According to the depth related to these zones, most of the facies that exist in these depths include sandstone and dolomite facies, and this is affected by the two factors of the primary sedimentary texture and the effect of the diagenesis process on them. Results can compared to the clustering zone determination in other nearby sandstone reservoirs without cores.

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“…Independently, an optimal number of clusters is computed based on the KRI. Eventually, the terminal clusters are constructed by merging the small clusters 1,5,6,9,18,26,34,42 .…”

Section: 2mrgc Clustering Methodsmentioning

confidence: 99%

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods

Eftekhari,

Memariani,

Maleki

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…So far, many studies have been carried out in the Dezful Embayment, Izeh, Fars, and the Persian Gulf area (Figure 1). These studies have shown a simple ramp or shelf profile for Sarvak depositional environment [40][41][42][43]. In the Lurestan Zone, the Late Albian-mid-Turonian, Sarvak carbonate factories were dominated by deeper platform environments and some special climatic conditions that led to different facies characteristics compared with other parts of the Zagros area [26] (Figures 1 and 2).…”

Section: Geological Settingmentioning

confidence: 99%

Evidence for Isolated Platform Development in the Cenomanian on the Passive Margin of Neotethys, Southwest Iran

2023

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In the Cenomanian, the southern passive margin of the Neotethys Ocean was dominated by a giant carbonate factory. This succession is known as Sarvak Formation, a significant reservoir in Iran. This study focuses on a detailed analysis of facies variations and paleoenvironmental reconstruction, including the interpretation of the platform types, during this time interval. Based on field observations and petrographical studies, 12 facies have been recognized and ascribed to six facies belts on a carbonate ramp. Sub-environments include the outer ramp and basin (distal open marine), talus and channel (mid-ramp) and lagoon and shoal (inner-ramp). The frequency of the facies and isochore maps indicate the paleoenvironmental conditions and their spatial variations in the study area. Based on all data and analyses, the suggested conceptual model for the Sarvak Formation in the Lurestan Zone is an isolated platform surrounded by two ramps. The upwind and downwind parts of these ramps were located in the central and northern sub-zones of the Lurestan Zone. This model can be used as a template for isolated platforms worldwide.

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“…Oliveira et al (2020) demonstrated that an inter-clustering process is recommended when selecting data points associated with representative volumes and local spots characterizing HFUs. In 2020, rock type and hydraulic flow units were used as a successful tool for reservoir characterization of the Bentiu-Abu Gabra sequence, Muglad basin, SW Sudan (El Sawy et al, 2020;Shalaby, 2021;Shoghi et al, 2020;Wu et al, 2020). Machine learning is effectively used by Man et al (2021) to boost the prediction of permeability and reduces uncertainty in reservoir modeling.…”

Section: Introductionmentioning

confidence: 99%

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units

Eftekhari,

Memariani,

Maleki

et al. 2023

Preprint

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Rock types are the reservoir's most essential properties and show special facies with a defined range of porosity and permeability. This study used the fuzzy c-means clustering technique to identify rock types in 280 core samples obtained from one of the wells drilled in the Asmari reservoir located in the Mansouri field. Four hydraulic flow units were determined for studied data after classifying the flow zone index with histogram analysis, normal probability analysis, and the sum of square error methods. Then the two methods of flow zone index and fuzzy c-means clustering were used to determine the rock types in given wells according to the results obtained from the implementation of these two methods in-depth, and continuity index acts, the fuzzy c-means methods with continuity number 3.12 compared to flow zone index with continuity number 2.77 shows more continuity in depth. Amounts of porosity and permeability of the different reservoir rock samples have high dispersion; the relationship between these two parameters improves by using hydraulic flow unit techniques significantly. In this study, the relationship between porosity and permeability of correlation coefficient improves and increases in each hydraulic flow unit by using the flow zone index method so that in the general case for all samples increased from 0.55 to 0.81 in the first hydraulic flow unit, 0.94 in the second hydraulic flow unit, 0.85 in the third hydraulic flow unit and 0.94 in the fourth hydraulic flow unit that this is because the samples were characterized by similar flow properties in a hydraulic flow unit. In comparison, the correlation coefficient is obtained less than the general case in the fuzzy c-means method in all hydraulic flow units.

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Facies modeling of synchronous successions - A case study from the mid-cretaceous of NW Zagros, Iran

Cited by 21 publications

References 24 publications

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods

Electrical facies of the Asmari Formation in the Mansouri oilfield, an application of multi-resolution graph-based and artificial neural network clustering methods

Evidence for Isolated Platform Development in the Cenomanian on the Passive Margin of Neotethys, Southwest Iran

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units

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