Laboratory Experiment, Production Performance Prediction Model, and Field Application of Multi-slug Microbial Enhanced Oil Recovery

• Published in: Energy & fuels Vol. 28; no. 10; pp. 6655 - 6665
• Main Authors: Cheng, Mingming, Lei, Guanglun, Gao, Jianbo, Xia, Tian, Wang, Hongsheng
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 16.10.2014
• Subjects: Applied sciences; Blocking; Crude oil, natural gas and petroleum products; Crude oil, natural gas, oil shales producing equipements and methods; Energy; Energy. Thermal use of fuels; Enhanced oil recovery; Enhanced oil recovery methods; Errors; Exact sciences and technology; Floods; Fuels; Mathematical models; Microorganisms; Oil recovery; Performance enhancement; Prospecting and production of crude oil, natural gas, oil shales and tar sands; Rock; Performance; Enhanced recovery
• ISSN: 0887-0624; 1520-5029
• DOI: 10.1021/ef5014083

Because of heterogeneous formations and multi-scale fractures, the accurate evaluation of microbial enhanced oil recovery is faced with numerous difficulties. For the purpose of evaluating the production performance of multi-slug microbial enhanced oil recovery, this work studied the influence of microbial activity on the properties of oil and porous rock and the effect of microbial slug compositions on oil recovery. A mathematical model was built on the basis of the experiment, using the Buckley–Leverett theory and production decline laws. The model is a combination of the characteristic curve of the water cut change and the exponential decline law of oil production, which could predict oilfield production performance, including water breakthrough time, cumulative oil production, and relationship between the water cut and water saturation of the flood front. In comparison to the numerical simulation method, this approach has no additional restrictions because of grid orientation effects, which were found to be suitable for predicting production performance of either large-scale or whole block. The predicted values of the model were compared to the measured values of a field test, indicating that the model predicted the performance of microbial enhanced oil recovery precisely. More specifically, the maximum prediction error of a single well was less than 10%, and the prediction error of the whole block was less than 3%, suggesting the suitability of the model in predicting production performance. In conclusion, it is believed that the multi-slug seems to be a better approach for enhanced oil recovery and that the mathematical model would accurately predict the production performance of microbial enhanced oil recovery.