Productivity Prediction Method of Shale Reservoir Based on Logging Data - A Block of Songliao Basin as an Example
Xu Zhang, Dong Li, Yu Pan, Weihua Liu
Abstract
Xu Zhang, Dong Li, Yu Pan, Weihua Liu
Abstract
Due to a small amount of test and dynamic data in the early development, it is unable to quickly and accurately predict the reservoir capacity. In this paper, we use the logging data of a block of sand four in Song Liao Basin to identify the evaluation methods that the key factors affecting the reservoir capacity. On this basis, the establishment of a relational model of reservoir oil permeability and productivity indices for predicting the reservoir capacity rapidly in early development. It has higher forecast accuracy by comparison with the measured values.
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Due to a small amount of test and dynamic data in the early development, it is unable to quickly and accurately predict the reservoir capacity. In this paper, we use the logging data of a block of sand four in Song Liao Basin to identify the evaluation methods that the key factors affecting the reservoir capacity. On this basis, the establishment of a relational model of reservoir oil permeability and productivity indices for predicting the reservoir capacity rapidly in early development. It has higher forecast accuracy by comparison with the measured values.
Key concepts: Petroleum engineering, Structural basin, Logging, Oil shale, Geology, Permeability (electromagnetism), Productivity, Reservoir modeling