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Work Flow Uses Vaca Muerta Data To Optimize Asset Evaluation

Asset evaluation embraces the integrated analysis of a hydrocarbon-bearing field, and the identification of suitable strategies for its future development, to add incremental value for the investor(s). Optimizing the evaluation process under uncertainty is important particularly in unconventional reservoirs, which hold large quantities of oil and gas resources but also exhibit large degrees of uncertainty. This paper describes a comprehensive optimization-under-uncertainty work flow that combines a simulation-based approach with semiautomatic work flows and high-speed computers to facilitate the process of decision-making for investors, using data from the Vaca Muerta Formation in Argentina as an example.

Introduction

An asset evaluation depends on many input parameters, some of which are partially known, partly analyzed, or unavailable. Yet a go/no-go decision must be made, frequently within short time frames, because of competition, changing conditions, or the chance to take advantage of the business opportunity. The decision usually is based on preliminary assumptions and a conscientious analysis of several possible outcomes. Identifying the suitable future development strategies and the estimation of uncertainties in the input variables is crucial. Knowing the possible variability of the input and how the field mechanisms function will allow probabilistic forecasts of parameters such as production, costs, prices, and revenues. In the case of unconventional reservoirs with very limited history and high development costs, optimization under uncertainty plays a significant role in maximizing profit, reducing investment risk, and facilitating the decision-making process.

The authors summarize the optimization-under-uncertainty work flow that was implemented for this study. The starting point is the development of a base-case, single-well, matched simulation model, and, where available, an extended model with history-matched offset wells. This is followed by sensitivity analysis to identify the most-influential parameters; uncertainty analysis and proxy modeling for developing probabilistic forecasting profiles (type wells); and optimization of key parameters under existing uncertainty, which is the final objective of this paper. The model and the uncertainty and optimization work flows have been built in the Petrel platform and all the simulations have been executed in the Eclipse compositional reservoir simulator, using published Vaca Muerta data.

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 191272, “Optimization Under Uncertainty for Reliable Unconventional Play Evaluation: A Case Study in Vaca Muerta Shale Gas Blocks, Argentina,” by Reza Mehranfar, Leonardo Marquez, SPE, Raphael Altman, SPE, Hassan Kolivand, Rodrigo Orantes, and Oswaldo Espinola, SPE, Schlumberger, prepared for the 2018 SPE Trinidad and Tobago Section Energy Resources Conference, Port of Spain, Trinidad and Tobago, 25–26 June. The paper has not been peer reviewed.
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Work Flow Uses Vaca Muerta Data To Optimize Asset Evaluation

01 July 2019

Volume: 71 | Issue: 7

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