Best Practices and Lessons Learned in the Construction and Maintenance of a Complex Gas Asset Integrated Production Model (IPM)

Abstract

Petroleum Experts' Integrated Production Model (IPM) suite of software is widely used in the E&P industry especially for project evaluations that require integration of both surface and subsurface models. There is evidence in the literature to show diverse applications in field development planning, integrated forecasting, surveillance and production system optimization. Perhaps less reported are the lessons learned and best practices in using the IPM software. This paper focuses on these issues using Chevron's IPM model for some of its largest gas fields.The Non-Operated Joint Venture (NOJV) Subsurface Team began developing an IPM model for one of its biggest gas assets in 2005. With explicit modeling of critical components like compressors, dozens of wells and reservoir tanks, platforms, fluid characterisation, gas-water contact movement, pipelines, sub-sea manifolds and separators, this is arguably the largest and most complex IPM model in Chevron. The model continues to play a critical role in Chevron's effective capital stewardship of the gas asset. The need to maintain the credibility of this model cannot be over-emphasized, and the model has undergone several phases of enhancement to ensure that it continues to meet business objectives.This paper describes some of the best practices and lessons learned in constructing and maintaining a complex IPM model. It is intended as a resource for IPM practitioners. Examples cover all aspects of the IPM from the non-technical (e.g. framing the problem, case definition and naming convention) to the technical (e.g. model construction, model maintenance, software limitations, constraint violations, production optimisation and quality assurance checks). IntroductionProduction forecasting involves attaching a timescale to production recovery and it is one of the most vital roles of reservoir engineering. It underpins the cashflow of any project and can make the difference between a project being sanctioned or abandoned. The complexity of the role is underscored by the requirement to integrate multiple and diverse disciplines including subsurface characterisation, surface network configuration, production philosophy, economic limits, business decisions and operational constraints.Unlike production forecasting for oil fields, gas forecasting is further complicated by long-term contracts and the need to meet contractual obligations. This requirement means that gas companies need to correctly predict the execution of future projects to ensure that they have enough gas to satisfy their contractual oligations. Usually, in gas forecasting, multiple fields with diverse fluid properties are produced simultaneously and this further introduces the complication of gas quality whilst also maximizing the value of by-products like condensate and natural gas liquids. These complexities indicate that an integrated gas forecasting model is required to accurately predict production for a gas field. There are many such products available including company proprietary software for internal us...

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