Application of Big Data to Carbonate Oil and Gas Field Exploitation

doi:10.11885/j.issn.1674-5086.2017.09.08.01

Abstract

Abstract: To solve the issue of arranging follow-up high-performance wells in the Ordovician carbonate oil and gas fields in the Tarim Basin, effective traps are recognized and classified based on detailed structural mapping. Statistical analyses of numerous drilling data were conducted to obtain oil and gas accumulation patterns and verify controls on structures in oil and gas reserves. The results reveal that the major types of structural traps in the study area can be divided into three main categories and six sub-categories. The three main categories are anticline traps, faulted anticline traps, and strike-slip fault-related faulted traps. The carbonate reservoir in the study area is, to a certain degree, continuous and inter-connected. Distributions of oil, gas, and water macroscopically and microscopically agree with the differential entrapment theory of oil and gas. Structural traps are regions where oil and gas are the most concentrated, and therefore should be prioritized for areas with concentrations of high-performance wells. Oil and gas accumulation modes can be classified into four types, accumulation within traps, fully filled slopes, partially filled slopes, and completely leaking slopes. Among these, fully filled slopes and accumulation within traps are the most favorable geological conditions for drilling and obtaining high-performance wells.

Key words: Ordovician system, big data, traps, structural oil/gas reservoirs, differential entrapment, accumulation patterns

CLC Number:

TE122

HAN Jie, ZHANG Shaowei, WU Jiangyong, CHEN Si, MA Xiaoping. Application of Big Data to Carbonate Oil and Gas Field Exploitation[J]. 西南石油大学学报(自然科学版), 2018, 40(6): 1-11.

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