基于神经网络的水泥浆配方智能推荐技术

Intelligent recommendation technology for cement slurryformula based on neural network

在大数据时代,数据的挖掘和分析是实现数据价值和影响决策的关键因素。将固井实验数据进行数字化、信息化的开发再利用是未来的必然走向。通过对固井水泥浆实验信息库进行分析,针对不同油田区块、不同地质条件,筛选出最适合的水泥浆配方范围,以达到对水泥浆配方的定向精简。并依托该模块所存储的实验数据池开展大量人工智能训练,形成水泥浆配方智能推荐技术。经现场试验应用,模型准确率达到了82.3%,该研究成果减少了人工繁杂的工作,提升数据传输及工作效率,一定程度上加快水泥浆配方调配周期,效果良好。

In the era of big data,data mining and analysis are key factors in achieving data value and influencing decision-making.The digitization and informatization development and reuse of cementing experiment data is an inevitable trend in the future.This article analyzes the information database of cementing cement slurry experiments and selects the most suitable range of cement slurry formulas for different oilfield blocks and geological conditions,in order to achieve targeted simplification of cement slurry formulas.And relying on the experimental data pool stored in this module,a large amount of artificial intelligence training is carried out to form an intelligent recommendation technology for cement slurry formulas.Through on-site testing and application,the accuracy of the model has reached 82.3%.The research results have reduced manual workload,improved data transmission and work efficiency,and to some extent accelerated the cement slurry formulation cycle,with good results.