Study Identifies the Seven Wastes of Reservoir Modeling Projects

Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 209566, “Overcoming the Seven Wastes of Reservoir Modeling Projects,” by Jon Sætrom and T.C. Sandø, Resoptima. The paper has not been peer reviewed. The complete paper evaluates learnings from the past 30 years of reservoir modeling projects in the oil and gas industry. Specifically, it considers methods aimed at quantifying uncertainty in the subsurface using multiple realizations, also known as ensemble-based methods. The authors highlight what they perceive to be the major challenges that companies currently face, which they call the “Seven Wastes of Reservoir Modeling Projects,” and outline potential ways to overcome these challenges based on lessons learned from more than 100 modeling projects worldwide during the past 10 years. The Challenge of Reservoir Modeling Reservoir modeling dictates that an effort must be made to solve an inverse problem wherein the unknown reservoir model components are assessed given measured static and dynamic data. The following three approaches to achieving this goal often are mentioned in the literature: - The base-case approach, in which a single best-guess estimate is built or a digital copy of the unknown reservoir parameters - The multiple stochastic approach, in which multiple models are built by generating realizations from the probability distribution of the unknown reservoir parameters using an automated framework - The multiple scenario approach, in which multiple (deterministic) models are built in a manual or semiautomated fashion The strengths and weaknesses of each method are detailed in the complete paper.