The Event Solution—A New Approach for Fully Integrated Studies Covering
Uncertainty Analysis and Risk Assessment

Elrafie, Emad A.; White, Jerry; Al-Awami, Fatema Hassan; Shenawi, Shamsuddin

doi:10.2523/105276-ms

Cited by 6 publications

(6 citation statements)

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“…They show a remarkable efficiency compared to other approaches. (Bustamante, Keller, & Monson, 2005) (Jutila & Goodwin, 2006) (Elrafie, White, & Awami, 2008) (Junker, Dose, Plas, & Little, 2006) (Gruenwalder, Poellitzer, & Clemens, 2007) (Elrafie, White, & Awami, 2008) (Shenawi, White, Elrafie, & El-Kilany, 2007).…”

Section: Approaches To History Matching and Uncertainty Quantificationmentioning

confidence: 99%

Bridging the Gap Between Deterministic and Probabilistic Uncertainty Quantification Using Advanced Proxy Based Methods

Goodwin

2015

SPE Reservoir Simulation Symposium

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The use of proxy models for optimisation of expensive functions has demonstrated its value since the 1990's in many industries. Within reservoir engineering, similar techniques have been used for over a decade for history matching, both in commercial tools and in-house software.In addition to efficient history matching, proxy models have a distinct advantage when performing uncertainty quantification of probabilistic forecasts. Markov Chain Monte Carlo (MCMC) methods cannot realistically be applied directly with reservoir simulations, and even fast proxy models can fail dramatically to adequately represent the range of uncertainty if implemented without due care.A pitfall of the use of proxy models is that they are considered 'black box' and their quality is difficult to measure. Engineers prefer to deal with deterministic simulation models which they can evaluate and understand.The main pitfall of simple random walk MCMC techniques, which have begun to appear within reservoir engineering workflows, is a focus on theoretical properties which are not observed in practical implementations. This gives rise to potential gross errors, which are not generally appreciated by practitioners. Advances in recent years within the field of Bayesian statistics have significantly improved this situation, but have not yet been disseminated within the oil and gas industry. This paper describes the limitations of random walk MCMC techniques which are currently used for reservoir prediction studies, and shows how Hamiltonian MCMC techniques, together with an efficient implementation of proxy models, can lead to a more reliable and validated probabilistic uncertainty quantification, whilst also generating a suitable ensemble of deterministic reservoir models. Scientific comparison studies are performed for both an analytical case and a realistic reservoir simulation case to demonstrate the validity of the approach.The benefit of this methodology is to allow asset teams to effectively manage reservoir decisions using a robust and validated understanding of uncertainty. It lays the scientific foundations for the next generation of uncertainty tools and workflows.

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Section: Approaches To History Matching and Uncertainty Quantificationmentioning

confidence: 99%

Bridging the Gap Between Deterministic and Probabilistic Uncertainty Quantification Using Advanced Proxy Based Methods

Goodwin

2015

SPE Reservoir Simulation Symposium

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“…in a timely manner to achieve certain objectives (increase recovery, net present value, ). These unknowns can expose corporations to unidentified subsurface risks and suboptimal developments (Elrafie et al 2007;Elrafie et al 2009). This challenge can now be even more complex with real-time data.…”

Section: Event Solution (Optimized Field Development Plans)mentioning

confidence: 99%

Overview of Saudi Aramco's Intelligent Field Program

et al. 2010

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Recent advancement in well technologies, communications and field instrumentation has made it possible to achieve total asset awareness and optimize operations over the field's development lifecycle. This is achieved by leveraging fields' real-time data for continuous monitoring and right-time response throughout the development processes. Right-time response has two components: Fast Interventions being done today as a product of an intra-process optimization, and Strategic Interventions based on more detailed modeling, discussed in the next steps section. The results of this integration have led to optimized drilling operations and well placements, increased production rates, and improved reservoir management and production operations. Real-time integration in the business processes, in turn, has introduced further opportunities for higher hydrocarbon recoveries and lower operating costs and capital expenditures.

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“…The scale, variety and complexity of uncertain factors from seismic to economics, however, has deterred even the most determined to conclude a practical integrated uncertainty and risk modeling solution 6 . Indeed, most known uncertainty management techniques consider only two possible approaches, namely, a deterministic realization to reflect reservoir physics and flow mechanisms with low and high values for all variables including uncertainty boundaries.…”

Section: Introductionmentioning

confidence: 99%

A Successful Process for Embracing Uncertainty and Mitigating Risk -From Geological Understanding to Development Plan Optimization of a Saudi Complex Reservoir

et al. 2008

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Integrated reservoir studies aim at synergizing all disciplines to form a reservoir understanding and best strategy to field development. Handling uncertainty and risk using probabilistic approach is a challenge since it becomes quickly overwhelming. This paper describes the approach used to handle uncertainty and risk in the Saudi Aramco Event Solution process. This approach lies in between the conventional deterministic approach where the team agrees on one realization and the probabilistic approach where a whole family of realizations is covering all possible outcomes. This paper describes the innovative Saudi Aramco Event Solution process 6 approach to jointly co-manage and model uncertainty and risk through an integrated static, dynamic and economic field development strategy process. This approach, that lies between a conventional deterministic and a fully probabilistic model approach, provides a range of qualified field development scenarios, under uncertainty and risk, including information and mitigation plans, in a reasonable timeframe (2-3 months).

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The Event Solution—A New Approach for Fully Integrated Studies Covering Uncertainty Analysis and Risk Assessment

Cited by 6 publications

References 0 publications

Bridging the Gap Between Deterministic and Probabilistic Uncertainty Quantification Using Advanced Proxy Based Methods

Bridging the Gap Between Deterministic and Probabilistic Uncertainty Quantification Using Advanced Proxy Based Methods

Overview of Saudi Aramco's Intelligent Field Program

A Successful Process for Embracing Uncertainty and Mitigating Risk -From Geological Understanding to Development Plan Optimization of a Saudi Complex Reservoir

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