Research on an Intelligent Method for Identifying Reservoir Thickness

Daqingchangyuan has formed a relatively perfect thickness division standard. However, its interpretation method is mainly one-dimensional or two-dimensional linear model. The multi-dimensional potential information of the curve itself and between the curves is not fully exploited. The interpretation method is not extensible. And the software platform used does not have the batch processing function, the interpretation efficiency is low. Based on this, this paper proposes a method of reservoir thickness division based on big data analysis. The method is based on abundant and complete logging data from Daqing Field. This method applies of multi-dimensional data correlation technology and cognitive computing technology. At the same time it integrates of expert experience and workflow. The thickness prediction model is established by machine learning. Automatic interpretation of Daqing Changyuan thickness has realized. It lays a solid foundation for logging intelligent comprehensive evaluation. The method has been applied to 209 wells in Changyuan County, Daqing, and the results are satisfactory. The method has been applied to the thickness division of 59271 wells in SA0 formation in Changyuan, Daqing. Figure 1 shows the interpretation of a well. It provides technical support for 3457.08 ten thousand tons proved reserves of Salto and Xingshugang oil field in 2022–2023.