Establishment and Application of Intelligent Laboratory for Reservoir Sensitivity Evaluation

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Abstract

In view of the shortcomings of traditional reservoir sensitivity evaluation experiments and the development needs of laboratories, the experimental technologies were optimized to realize the efficient collection, storage, management and application of experimental data, improve the quality of experimental analysis, reduce labor intensity, improve work efficiency and standardize the daily management of the laboratories. For this purpose, an intellectualized reservoir sensitivity evaluation system was designed. Taking modularization, miniaturization, integration, automation and specialization as the design concept, taking the industry standard and operation document of reservoir sensitivity evaluation as the data output standard of the new equipment, the equipment manufacturers and experimental experts who are engaged in reservoir sensitivity evaluation all the year round designed the reservoir sensitivity evaluation system through the process design, component design, structural design and assembly effect simulation. The system includes modularized and integrated equipments, standardized programmatic procedure and shared platform of testing process and data. It has the ability of automatic data acquisition, analysis and processing, safety warning, process tracking and intelligent process discrimination. Through automatic control, the experimental process is optimized, the experimental data of sensitivity evaluation are enriched, the accuracy and systematicness of sensitivity evaluation are enhanced, rapid and accurate information is provided for production management and scientific decision-making in oilfield, the timeliness of macroscopic decision-making is enhanced, and the period from sensitivity research to decision-making is shortened.

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Guo, H. ying, Xu, N., Li, Q., Liu, S., & Zheng, H. yan. (2020). Establishment and Application of Intelligent Laboratory for Reservoir Sensitivity Evaluation. In Springer Series in Geomechanics and Geoengineering (pp. 1230–1239). Springer. https://doi.org/10.1007/978-981-15-2485-1_109

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