ESTIMATION OF RESERVOIR LITHOLOGY BASED ON LOG DATA USING ARTIFICIAL NEURAL NETWORK METHOD

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DEZFOOLIAN MOHAMMAD AMIN; NABI BIDHENDI MAJID; MEMARIANI MAHMOUD

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Journal: JOURNAL OF THE EARTH Year:2010 | Volume:5 | Issue:1 (SPECIAL EDITION) Page(s): 13-23

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Title

ESTIMATION OF RESERVOIR LITHOLOGY BASED ON LOG DATA USING ARTIFICIAL NEURAL NETWORK METHOD

Author(s)

DEZFOOLIAN MOHAMMAD AMIN | NABI BIDHENDI MAJID | MEMARIANI MAHMOUD | Issue Writer Certificate

Keywords

HYDROCARBON RESERVOIRQ2

ARTIFICIAL NEURAL NETWORKQ2

LITHOLOGYQ2

COREQ2

WELL LOGQ3

Abstract

We use CORE analysis and well testing to determinate the reservoir LITHOLOGY. Unfortunately, coring from each wells in large oil fields such as Iran oil fields, is very expensive. However, because of the importance of this information which is obtained from LITHOLOGY, it is necessary to coring from some of the reservoir wells.Purpose of this study is prediction of HYDROCARBON RESERVOIR LITHOLOGY in South Pars field using ARTIFICIAL NEURAL NETWORK with back propagation error algorithm (BP) and Trainlm algorithm with Matlab software from wire-line logs including gamma ray, density, neutron, sonic and photoelectric (PE). This method can reduce requirement of coring and reduce the costs. The area we have studied, consist of three lithologies, including Dolomite, shale and Anhydrite. The regression between the predicted and the real values of volume concentrations of Dolomite, shale and Anhydrite are obtained respectively, as 0.87, 0.76 and 0.90. The results show that the neural network gives a reasonable estimation for LITHOLOGY.

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APA: Copy

DEZFOOLIAN, MOHAMMAD AMIN, NABI BIDHENDI, MAJID, & MEMARIANI, MAHMOUD. (2010). ESTIMATION OF RESERVOIR LITHOLOGY BASED ON LOG DATA USING ARTIFICIAL NEURAL NETWORK METHOD. JOURNAL OF THE EARTH, 5(1 (SPECIAL EDITION)), 13-23. SID. https://sid.ir/paper/192941/en

Vancouver: Copy

DEZFOOLIAN MOHAMMAD AMIN, NABI BIDHENDI MAJID, MEMARIANI MAHMOUD. ESTIMATION OF RESERVOIR LITHOLOGY BASED ON LOG DATA USING ARTIFICIAL NEURAL NETWORK METHOD. JOURNAL OF THE EARTH[Internet]. 2010;5(1 (SPECIAL EDITION)):13-23. Available from: https://sid.ir/paper/192941/en

IEEE: Copy

MOHAMMAD AMIN DEZFOOLIAN, MAJID NABI BIDHENDI, and MAHMOUD MEMARIANI, “ESTIMATION OF RESERVOIR LITHOLOGY BASED ON LOG DATA USING ARTIFICIAL NEURAL NETWORK METHOD,” JOURNAL OF THE EARTH, vol. 5, no. 1 (SPECIAL EDITION), pp. 13–23, 2010, [Online]. Available: https://sid.ir/paper/192941/en

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