ESTIMATION OF PERMEABILITY BY USING HYDRAULIC FLOW UNITS AND ARTIFICIAL NEURAL NETWORKS IN THE DAIRYMAN FORMATION AS RESERVOIR LOCATED IN THE RESHADAT OIL FIELD

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RESALAT F.; MOUSAVI ROHBAKHSH M.; AALI J.; ZARE S.

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Journal: JOURNAL OF GEOTECHNICAL GEOLOGY (APPLIED GEOLOGY) Year:2012 | Volume:8 | Issue:1 Page(s): 27-34

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Title

ESTIMATION OF PERMEABILITY BY USING HYDRAULIC FLOW UNITS AND ARTIFICIAL NEURAL NETWORKS IN THE DAIRYMAN FORMATION AS RESERVOIR LOCATED IN THE RESHADAT OIL FIELD

Author(s)

RESALAT F. | MOUSAVI ROHBAKHSH M. | AALI J. | ZARE S. | Issue Writer Certificate

Keywords

FLOW ZONE INDEXQ2

WELL LOGGINGQ2

CORE OPERATIONSQ2

DARIYAN CARBONATE FORMATION AS RESERVOIRQ2

Abstract

One of the important parameters to describe and examine the production of the reservoir is the permeability. Permeability is conventionally estimated by using core and WELL LOGGING data. CORE OPERATIONS are expensive. So, the possibility of performing them in all wells of a field does not exist. In recent years, the method of hydraulic flow units and Intelligent Systems such as neural networks to estimate the reservoir parameters has been very significant progress. This study has been done on the Dariyan Carbonate Formation which is reservoir in the Reshadat oil field. First, the FLOW ZONE INDEX (FZI) has been determined by using the method of artificial neural networks and core data in existing wells and FZI has been generalized and calculated for wells without core. Finally, permeability has been estimated by the hydraulic flow units using artificial neural networks in the wells without core. The correlation coefficient between core permeability and permeability results calculated by combining the two approaches of hydraulic flow units and neural networks is R2=0.87 and by using artificial neural networks is R2=0.82 which shows the accuracy of the hydraulic units for improving the estimation of permeability.

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APA: Copy

RESALAT, F., MOUSAVI ROHBAKHSH, M., AALI, J., & ZARE, S.. (2012). ESTIMATION OF PERMEABILITY BY USING HYDRAULIC FLOW UNITS AND ARTIFICIAL NEURAL NETWORKS IN THE DAIRYMAN FORMATION AS RESERVOIR LOCATED IN THE RESHADAT OIL FIELD. JOURNAL OF GEOTECHNICAL GEOLOGY (APPLIED GEOLOGY), 8(1), 27-34. SID. https://sid.ir/paper/127094/en

Vancouver: Copy

RESALAT F., MOUSAVI ROHBAKHSH M., AALI J., ZARE S.. ESTIMATION OF PERMEABILITY BY USING HYDRAULIC FLOW UNITS AND ARTIFICIAL NEURAL NETWORKS IN THE DAIRYMAN FORMATION AS RESERVOIR LOCATED IN THE RESHADAT OIL FIELD. JOURNAL OF GEOTECHNICAL GEOLOGY (APPLIED GEOLOGY)[Internet]. 2012;8(1):27-34. Available from: https://sid.ir/paper/127094/en

IEEE: Copy

F. RESALAT, M. MOUSAVI ROHBAKHSH, J. AALI, and S. ZARE, “ESTIMATION OF PERMEABILITY BY USING HYDRAULIC FLOW UNITS AND ARTIFICIAL NEURAL NETWORKS IN THE DAIRYMAN FORMATION AS RESERVOIR LOCATED IN THE RESHADAT OIL FIELD,” JOURNAL OF GEOTECHNICAL GEOLOGY (APPLIED GEOLOGY), vol. 8, no. 1, pp. 27–34, 2012, [Online]. Available: https://sid.ir/paper/127094/en

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