Probabilistic Prediction of Multi-Wells Production Based on Production Characteristics Analysis Using Key Factors in Shale Formations

Energies

Hyo-Jin Shin¹  Jong-Se Lim¹  Il-Sik Jang² 

[1] Department of Energy & Resources Engineering, Korea Maritime & Ocean University, Busan 49112, Korea;Department of Energy Resources Engineering, Chosun University, Gwangju 61452, Korea;

关键词: shale formation;    probabilistic prediction;    production characteristics;    key factors;    multi-wells;   

DOI  :  10.3390/en14175226

来源: DOAJ

【 摘 要 】

In this study, we propose a novel workflow to predict the production of existing and new multi-wells. To perform reliable production forecasting on heterogeneous shale formations, the features of these formations must be analyzed by classifying the formations into various groups; the groups have different production characteristics depending on the key factors that affect the shale formation. In addition, the limited data obtained from nearby existing multi-wells should be used to estimate the production of new wells. The key factors that affect shale formation were derived from the correlation and principal component analysis of available production-related attributes. The production of existing wells was estimated by classifying them into groups based on their production characteristics. These classified groups also identified the relationship between hydraulic fracturing design factors and productivity. To estimate the production of new wells (blind wells), we generated groups with different production characteristics and leveraged their features to estimate the production. Probabilistic values of the group features were entered into the input layer of the artificial neural network model to consider the variation in the production of shale formations. All the estimated productions exhibited less error than the previous analytical results, suggesting the utilization potential of the proposed workflow.

【 授权许可】

Unknown