Estimation of geomechanical units using petrophysical logs, core and supervised intelligent committee machine method to optimize exploration drilling operations

Pourreza, Soheyl; Hajizadeh, Farnusch; Kadkhodaie, Ali

doi:10.1007/s12517-023-11223-5

“…Clustering seeks to divide the data into clusters that maximize the similarity between the data within each cluster and the similarity between the data within the different clusters. A fuzzy c-means clustering method has been proposed to solve the problem of assigning each data to a particular cluster in each iteration (Bezdek, 1981;Ghadami et al, 2015;Kadkhodaie-Ilkhchi et al, 2010;Kadkhodaie and Amini, 2008;Olayiwola and Sanuade, 2021;Pourreza et al, 2023;Salavati et al, 2023;Shakiba et al, 2015;Tian et al, 2016). In FCM, the objective is to minimize the Eq.…”

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 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

“…Each data point belongs to a cluster center with a degree which is determined by the membership grade. A fuzzy c-means clustering method has been proposed to solve the problem of assigning each data to a particular cluster in each iteration (Bezdek, 1981;Ghadami et al, 2015;Kadkhodaie-Ilkhchi et al, 2010;Kadkhodaie and Amini, 2008;Olayiwola and Sanuade, 2021;Pourreza et al, 2023;Salavati et al, 2023;Shakiba et al, 2015;Tian et al, 2016). In fuzzy clustering, an object can be a member of more than one cluster.…”

Section: Fuzzy C-means Methodsmentioning

confidence: 99%

“…Individual data point belongs to a cluster center with a degree defined by the membership grade. A fuzzy c-means clustering method has been proposed to decipher the issue of allocating each data to a particular cluster in each iteration 105,[111][112][113][114] .…”

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 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

Development of rheological models depending on the time, temperature, and pressure of wellbore cement compositions: a case study of southern Iran’s exploratory oilfields

Saffari,

Ameri,

Jahangiri

et al. 2024

Arab J Geosci

5

0

View full text Add to dashboard Cite

Estimation of geomechanical units using petrophysical logs, core and supervised intelligent committee machine method to optimize exploration drilling operations

Cited by 7 publications

References 42 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

Development of rheological models depending on the time, temperature, and pressure of wellbore cement compositions: a case study of southern Iran’s exploratory oilfields

Contact Info

Product

Resources

About