Integrated Reservoir Studies - Roll-Up Initiative
Authors: Denney Dennis 
Published: February 2015

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 138551, ’Integrated Reservoir Studies - Roll-Up Initiative: A New Industry Step-Change Innovation,’ by Emad Elrafie, SPE, Martin Hogg, SPE, and Hisham Mohammadi, Saudi Aramco, prepared for the 2010 Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 1-4 November. The paper has not been peer reviewed.
An enormous volume of data, models, and decisions is generated and gathered in every integrated study. The ability and opportunity for a multidisciplinary project team, including management, to browse, review, visualize, and analyze in-progress and final cross-discipline study results easily and in a fast, responsive, and easily comprehendible manner do not readily exist. A studies-decision-synergy (SDS) initiative in Saudi Aramco was developed (technology and process), and study improvement (technical workflows, study decisions, and results) is presented.
Introduction
The industry has an established optimized-field-development-plan (OFDP) track record. Projects range from simple (e.g., a few wells with limited uncertainties and short production history) to complex (e.g., hundreds of wells with a long production history, complex well types, multiple decision alternatives, and a wide range of associated modeling uncertainties). In general, the reliability and confidence level of simple-predictive-model quality with limited uncertainties is relatively high. In contrast, an acceptable confidence level for complex-predictive-model quality and large uncertainties has yet to be reached. The quality problem of complex models is attributed to very large data sets, multiple study-decision alternatives, hundreds of uncertainty arrays, and existing industry technology and process deficiencies in the delivery of a practical high-quality modeling solution that incorporates integrated SDS across all disciplines and management. Consequently, and in the absence of complete technological solutions, industry has explored and developed alternative practices (i.e., top-down, bottom-up, and event-solution approaches) to accommodate the challenge of delivering a complex OFDP recommendation where multiple uncertainties exist.
In a top-down-modeling approach, the range of uncertainty factors that could affect an OFDP recommendation is screened into a manageable number of modeling alternatives by a group of company experts and tools. Typically, simple models are constructed that calculate economic yardsticks. Subsurface uncertainty is supported by a minimal set of simple simulation runs. As critical project uncertainty factors become clear, more model detail is added to the original models. The benefit of the top-down approach is the ability to navigate and process a list of possible decisions rapidly. The risks of this approach are a heavy reliance on expert-selected scenarios that may not deliver the ultimate optimal development decision and subsurface uncertainty that is defined almost a priori.
The bottom-up concept seeks to undertake complete modeling and simulation efforts with all potential OFDP-study uncertainties, decisions, and associated combinations. This modeling task is overwhelming and not appropriate for models that take longer than a few minutes to run. Therefore, the most common approach is to ignore uncertainty and undertake single simulations for one subsurface-uncertainty parameter at a time. Computationally, such an approach is daunting and likely to require a significant number of simulation runs to achieve a project outcome.