COINCIDENCE BETWEEN GEOCHEMICAL AND PERTOPHYSICAL DATA USING ARTIFICIAL NEURAL NETWORK AND CLUSTER ANALYSIS IN AZADEGAN OIL FIELD

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GHOLIPOUR SIROUS; KADKHODAEI ALI; TAHMOURESI MOHAMMAD ALI; MOMENZADEH HAMID

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Journal: PETROLEUM RESEARCH Year:2016 | Volume:26 | Issue:86 Page(s): 22-32

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Title

COINCIDENCE BETWEEN GEOCHEMICAL AND PERTOPHYSICAL DATA USING ARTIFICIAL NEURAL NETWORK AND CLUSTER ANALYSIS IN AZADEGAN OIL FIELD

Author(s)

GHOLIPOUR SIROUS | KADKHODAEI ALI | TAHMOURESI MOHAMMAD ALI | MOMENZADEH HAMID | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKQ2

TOCQ2

AZADEGAN OIL FIELDQ2

PETROPHYSICAL DATAQ1

CLUSTER ANALYSISQ2

Abstract

One of the major geochemical parameters is total organic carbon (TOC) which is used to evaluate hydrocarbon generation potential of source rocks.Measurement of such important parameter requires performing tests on small-scale drill cuttings which is too expensive and they are measured on a limited number of samples. However, PETROPHYSICAL DATA are measured for all drilled wells in a hydrocarbon field. In this paper, the ARTIFICIAL NEURAL NETWORK technology was used to estimate TOC from petrophysical logs. The correlation coefficient between the estimated TOC from neural network and measured data from Rock-Eval pyrolysis is 71% which is an acceptable value.Then, the estimated total organic carbon log is used to identify the organic facies with a maximum amount of TOC. The methodology used in this paper is CLUSTER ANALYSIS that includes MRGC and AHC methods. The results of these two methods are compared and evaluated based on cluster validity test and the best method of data clustering was used to cluster PETROPHYSICAL DATA into certain facies. The results showed that the MRGC clustering provides better results with higher accuracy. Moreover, using this method has advantages in comparison to AHC for determination of organic facies and has capabilities to provide high resolution clusters. The presented methodology was explained by using a case study from one well of Azadegan field, Abadan plain.

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APA: Copy

GHOLIPOUR, SIROUS, KADKHODAEI, ALI, TAHMOURESI, MOHAMMAD ALI, & MOMENZADEH, HAMID. (2016). COINCIDENCE BETWEEN GEOCHEMICAL AND PERTOPHYSICAL DATA USING ARTIFICIAL NEURAL NETWORK AND CLUSTER ANALYSIS IN AZADEGAN OIL FIELD. PETROLEUM RESEARCH, 26(86), 22-32. SID. https://sid.ir/paper/115166/en

Vancouver: Copy

GHOLIPOUR SIROUS, KADKHODAEI ALI, TAHMOURESI MOHAMMAD ALI, MOMENZADEH HAMID. COINCIDENCE BETWEEN GEOCHEMICAL AND PERTOPHYSICAL DATA USING ARTIFICIAL NEURAL NETWORK AND CLUSTER ANALYSIS IN AZADEGAN OIL FIELD. PETROLEUM RESEARCH[Internet]. 2016;26(86):22-32. Available from: https://sid.ir/paper/115166/en

IEEE: Copy

SIROUS GHOLIPOUR, ALI KADKHODAEI, MOHAMMAD ALI TAHMOURESI, and HAMID MOMENZADEH, “COINCIDENCE BETWEEN GEOCHEMICAL AND PERTOPHYSICAL DATA USING ARTIFICIAL NEURAL NETWORK AND CLUSTER ANALYSIS IN AZADEGAN OIL FIELD,” PETROLEUM RESEARCH, vol. 26, no. 86, pp. 22–32, 2016, [Online]. Available: https://sid.ir/paper/115166/en

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