Identification of electrical and petrophysical rock types based on core and well logs: Utilizing the results to delineate prolific zones in deep water sandy packages from the Shah Deniz gas field in the south Caspian Sea basin

Jafarzadeh, Najmeh; Kadkhodaie, Ali; Ahmad, Behnam Jan; Kadkhodaie, Rahim; Karimi, Mahdokht

doi:10.1016/j.jngse.2019.102923

“…The quality of this algorithm strongly depends on the initial number of clusters and the initial location of the cluster centers. As seen in Table 3, the fuzzy c-means tries to minimize Jm with successive iterations until a significant improvement is achieved (Jafarzadeh et al, 2019;Kadkhodaie-Ilkhchi et al, 2013;Kadkhodaie and Amini, 2008;Kadkhodaie and Kadkhodaie, 2018;Kadkhodaie et al, 2006;Kiaei et al, 2015).…”

Section: Fuzzy C-means Methodsmentioning

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

0

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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 from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. 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. The relationship between porosity and permeability improved using hydraulic flow unit techniques significantly. In this study, the correlation coefficient between porosity and permeability improves and increases in each hydraulic flow unit using the flow zone index method. So that in the general case, all samples increased from 0.55 to 0.81 in the first hydraulic flow unit and finally 0.94 in the fourth hydraulic flow unit. 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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“…In the FCM fuzzy clustering algorithm, the number and centers of the clusters are first determined by the user. The quality of this algorithm strongly depends on the initial number of clusters and the initial location of the cluster centers (Jafarzadeh et al, 2019;Kadkhodaie-Ilkhchi et al, 2013;Kadkhodaie and Amini, 2008;Kadkhodaie and Kadkhodaie, 2018;Kadkhodaie et al, 2006;Kiaei et al, 2015).…”

Section: Fuzzy C-means Methodsmentioning

confidence: 99%

“…However, unfortunately, in most cases, this convergence does not lead to the general minimum and stops at the first local minimum. For this reason, the FCM algorithm is sensitive to the selection of initial values, and therefore a random selection of initial values leads to unfavorable performance of the algorithm (Bezdek, 1981;Hosseini et al, 2023a;Jafarzadeh et al, 2019;Kadkhodaie and Amini, 2008;Kadkhodaie et al, 2006;Majdi and Beiki, 2019;Shakiba et al, 2015). The general purpose of conducting this study is to determine the final model of reservoir modeling and sedimentary environment for the Asmari reservoir in the Mansouri field, utilizing techniques to identify rock typing, flow units, and electrofacies.…”

Section: Introductionmentioning

confidence: 99%

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units in the Asmari Formation, SW Iran

Eftekhari,

Memariani,

Maleki

et al. 2023

Preprint

0

View full text Add to dashboard Cite

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 from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. 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. The relationship between porosity and permeability improved using hydraulic flow unit techniques significantly. In this study, the correlation coefficient between porosity and permeability improves and increases in each hydraulic flow unit using the flow zone index method. So that in the general case, all samples increased from 0.55 to 0.81 in the first hydraulic flow unit and finally 0.94 in the fourth hydraulic flow unit. 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.

show abstract

“…The quality of this algorithm strongly depends on the initial number of clusters and the initial location of the cluster centers. As seen in Table 3, the fuzzy c-means tries to minimize Jm with successive iterations until a significant improvement is achieved (Jafarzadeh et al, 2019;Kadkhodaie-Ilkhchi et al, 2013;Kadkhodaie & Amini, 2008;Kadkhodaie & Kadkhodaie, 2018;Kadkhodaie et al, 2006;Kiaei et al, 2015). As seen in Fig.…”

Section: Fuzzy C-means Methodsmentioning

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

0

View full text Add to dashboard Cite

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.

show abstract

Identification of electrical and petrophysical rock types based on core and well logs: Utilizing the results to delineate prolific zones in deep water sandy packages from the Shah Deniz gas field in the south Caspian Sea basin

Cited by 30 publications

References 14 publications

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

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

Determining the petrophysical rock types utilizing the Fuzzy C-means Clustering technique and the concept of hydraulic flow units in the Asmari Formation, SW Iran

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

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