Unravel the Lacustrine Shale Oil Reservoir Potential in China by Integrating Advanced Logging Technologies and Special Core Measurements
- Guoqiang Liu (PetroChina Exploration and Production Company) | Yuting Hou (PetroChina Changqing Oilfield Company) | Junling He (PetroChina Jilin Oilfield Company) | Hao Zhang (PetroChina Xinjiang Oilfield Company) | Jinlong Wu (Schlumberger) | Xianran Zhao (Schlumberger) | Huayang Li (Schlumberger) | Fangfang Wu (Schlumberger) | Shenzhuan Li (Schlumberger) | Yuxi Wang (Schlumberger)
- Document ID
- International Petroleum Technology Conference
- International Petroleum Technology Conference, 26-28 March, Beijing, China
- Publication Date
- Document Type
- Conference Paper
- 2019. International Petroleum Technology Conference
- 5.1 Reservoir Characterisation, 5.5.2 Core Analysis, 7.4.1 Resource Potential and Evaluation, 5.6.2 Core Analysis, 5.1 Reservoir Characterisation, 7 Management and Information, 7.4 Energy Economics, 5.8.4 Shale Oil, 5.1.1 Exploration, Development, Structural Geology, 5.6 Formation Evaluation & Management, 1.6 Drilling Operations, 5 Reservoir Desciption & Dynamics, 1.6.9 Coring, Fishing, 5.8 Unconventional and Complex Reservoirs, 4.3.4 Scale
- Advanced Logging Technologies, Lacustrine Deposit, China, Shale Oil Reservoir, Special Core Measurement
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Most shale oil resources in China are lacustrine deposit. The reservoirs are usually characterized by complex lithology and high heterogeneity with various mineral compositions (quartz, carbonates, feldspars, pyrites and volcanic ash), total organic carbon and pore structure. How to delineate the shale oil reservoir, how to identify the ‘sweet spots’ and its distribution are the two major challenges and objectives for this study.
To answer the question, a systematic workflow was proposed by integrating the advanced logging technologies (such as nuclear magnetic resonance, micro-resistivity imager, spectroscopy data, array dielectric tool) with special core measurement data. Firstly, the shale oil reservoir was classified into different types according to the logging responses. Secondly, core samples were chosen from each type and sent out to lab for a series of core special experiments to test the microscopic properties. Finally, the advanced core analysis results and logging technologies were integrated to depict the characters of the different types of shale oil reservoirs from microscopic to macroscopic scale. And by comparing with testing data, the features of best shale oil reservoir type can be identified, and the distribution and potential of shale oil reservoir can be unraveled.
The new approach helped to get a thorough understanding of the shale oil reservoirs characteristics, such as lithology, mineral composition, pore types, pore size distribution, oil content, kerogen type and maturity of organic matter, organic carbon content and distribution. Six different kinds of shale oil reservoir facies were classfied from loging responses, inculding super high gamma ray siliceous shale, high gamma ray siliceous shale, high gamma ray argillaceous shale, high gamma ray tuffaceous shale, medium gamma ray siliceous shale and medium gamma ray argillaceous shale. High gamma ray siliceous shale and medium gamma ray siliceous shale are proved to be the best shale oil reserovir, which contains 2~8% of TOC, 2~12% of effective porosity, more than 50% of quartz content and high propotion of macropores.
The method proposed in this project has been implemented in many unconventional reservoirs in china to evaluate the resource potential and get a comprehensive understanding of the shale oil reservoir.
The wells tested based on the recommendation has got promising production after fracturing, which brought client big confidence for future exploration.
|File Size||2 MB||Number of Pages||12|