Characterization of a heterogeneous carbonate reservoir by integrating electrofacies and hydraulic flow units: a case study of Kangan gas field, Zagros basin

被引:0
作者
Amir Karimian Torghabeh
Jafar Qajar
Ali Dehghan Abnavi
机构
[1] Shiraz University,Department of Earth Sciences, Faculty of Sciences
[2] Shiraz University,Department of Petroleum Engineering, School of Chemical and Petroleum Engineering
来源
Journal of Petroleum Exploration and Production Technology | 2023年 / 13卷
关键词
Electrofacies; Hydraulic flow units; MRGC method; Cluster analysis; Carbonate reservoirs;
D O I
暂无
中图分类号
学科分类号
摘要
Reservoir characterization is one of the key stages in oil and gas exploration, appraisal, development, and optimal production. During the exploration phase, core analysis and well logging are basic information obtained after the pay zone identification. This study aims to integrate the concept of electrofacies (EFs) with hydraulic flow units (HFUs) to effectively characterize Permo–Triassic carbonate formations at the Kangan giant gas field in southwestern Iran. For this purpose, well log data collected from 10 drilled wellbores and 490 core data have been analyzed based on similar clusters and statistical features in which rock-type approaches were used in order to integrate petrophysical data with facies. In particular, we used a multi-resolution graph-based clustering (MRGC) method to determine EFs and the probability plot method, histogram analysis, and the plot of reservoir quality index versus the normalized porosity to identify HFUs. Based on the data, five electrofacies and six HFUs were identified. To establish a good connection between the electrofacies and the pay zones, we analyzed wells’ cross sections to compare lithology, production potential in each zone, rock type, and amount of shale and eventually to adapt facies to flow units and determine the best quality reservoir zone. The main difference between this work and other studies in the literature is adopting a systematic approach based on integrating the geology (via EFs analysis) and engineering examination (via HFUs) to accurately characterize the hydrocarbon-bearing formations. The results of this study help in rapid and cost-effective carbonate reservoir characterization by combining electrofacies clustering and HFU analysis based on core and log data, which are available and routine information in all oil/gas fields. This, in turn, assists in developing the field, using more appropriate production and EOR scenarios, and even locating proper perforation sites.
引用
收藏
页码:645 / 660
页数:15
相关论文
共 76 条
[11]  
Doveton JH(1984)Geological factors influencing reservoir performance of the Hartzog draw field Wyoming J Petrol Technol 11 75-1094
[12]  
Borgomano JRF(2006)Upper Dalan Member and Kangan formation between the Zagros Mountains and offshore Fars, Iran: depositional system, biostratigraphy and stratigraphic architecture GeoArabia 16 257-120
[13]  
Fournier FO(2013)New approach in permeability and hydraulic-flow-unit determination SPE Reservir Eval Eng 176 1082-402
[14]  
Viseur S(2019)An effective approach to generate drainage representative capillary pressure and relative permeability curves in the framework of reservoir electrofacies J Petrol Sci Eng 111 106-57
[15]  
Rijkels L(2013)Analysis of the reservoir electrofacies in the framework of hydraulic flow units in the Whicher Range Field, Perth Basin, Western Australia J Petrol Sci Eng 6 393-22
[16]  
Chekani M(2014)Electrofacies in gas shale from well log data via cluster analysis: a case study of the Perth Basin West Aust Open Geosci 2 50-191
[17]  
Kharrat R(2012)Assessment of clustering methods for predicting permeability in a heterogeneous carbonate reservoir J Pet Sci Technol 27 3-982
[18]  
Ebanks JWJ(1995)Estimating spatial distributions of heterogeneous subsurface characteristics by regionalized classification of electrofacies Math Geol 38 177-235
[19]  
El Sharawy MS(2015)Determining hydraulic flow units using a hybrid neural network and multi-resolution graph-based clustering method: case study from south pars gasfield Iran J Petrolum Geol 9 974-497
[20]  
Nabawy BS(2012)Prediction of PEF and LITH logs using MRGC approach Life Sci J 167 103868-131