(589c) Production Estimation and Well Classification for Hydraulically Fractured Horizontal Wells: A Data-Driven Model-Based Approach
AIChE Annual Meeting
Wednesday, November 1, 2017 - 3:59pm to 4:21pm
There are numerous techniques for developing data-driven models. They all combine art with science. An approach that is first explored in this research is PLS (Partial Least Squares) to build a model connecting various input variables (such reservoir properties, wellbore geometry, fracture construction process, and others) with production. Given that production varies with time, a second target is the development of a dynamic model, capturing the effect of decision variables on production over time. Sensitivity analysis of decision variables is carried out to identify variables with high impact. The VIP (variable importance in projection) statistic is explored to that end.
The data-driven models developed will be useful for design purposes and what-if analyses. They can also provide insight into the variables that have strong impact on fractured horizontal well performance. Therefore, the proposed models are envisioned to offer initial decision support for any fracturing operation. In addition, they may will also be able to indicate parameters that should be improved/modified to get desired results in existing wells.
Future refinements of the proposed approach include the development of nonlinear models from a variety of well established multivariate statistical methods.
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