Application of Big Data Water Distribution Technology in T Block of Q Oilfield

Abstract

With the extension of oilfield development time, a large amount of production data has been accumulated in the oilfield water injection development process, which brings great challenges and opportunities to the adjustment analysis, diagnosis, and optimization of oilfield development [1]. Based on geological static data, historical data such as production and monitoring at both ends of injection and production, and using big data and deep learning methods, this paper forms a big data analysis method for water injection optimization with the mode of “finding key layers of key wells, implementing key monitoring and deciding the best scheme”. Good results have been achieved in guiding the adjustment of single well water quantity in Block T of Q Oilfield. Eight water injection adjustment schemes have been deployed on-site, 16 intervals have been adjusted, and the daily water injection has been adjusted from 136 cubic meters to 120 cubic meters. After adjustment, the accumulated oil in the connected oil well stage has increased by 262.3 tons, and the production decline in the well area has been effectively controlled, which provides new technologies and new ideas for the dynamic development adjustment of the oilfield.