A review of closed-loop reservoir management

Hou, Jirui; Zhou, Kang; Zhang, Xian-Song; Kang, Xiaodong; Xie, Hai Long

doi:10.1007/s12182-014-0005-6

Cited by 56 publications

(24 citation statements)

References 135 publications

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“…While this is an area of active research [24,65], validation of closed loop reservoir management on real field data is an area of particular interest.…”

Section: Discussionmentioning

confidence: 99%

“…Future work recommendations in optimization methods and applications are made. Where a specific topic is too broad to cover in this review, related review papers [17][18][19][20][21][22][23][24] provide further detail for the interested reader. In particular, one area of active research related to production optimization is the quantification of uncertainty, this is reviewed by Oliver and Chen [22].…”

Section: Introductionmentioning

confidence: 99%

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Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

et al. 2017

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This paper presents a review of history matching and oil field development optimization techniques with a focus on optimization algorithms. History matching algorithms are reviewed as a precursor to production optimization algorithms. Techniques for history matching and production optimization are reviewed including global and local methods. Well placement, well control, and combined well placement-control optimization using both secondary and tertiary oil production techniques are considered. Secondary and tertiary recovery techniques are commonly referred to as waterflooding and enhanced oil recovery (EOR), respectively. Benchmark models for comparison of methods are summarized while other applications of methods are discussed throughout. No single optimization method is found to be universally superior. Key areas of future work are combining optimization methods and integrating multiple optimization processes. Current challenges and future research opportunities for improved model validation and large scale optimization algorithms are also discussed.

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“…While this is an area of active research [24,65], validation of closed loop reservoir management on real field data is an area of particular interest.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

et al. 2017

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“…, Naevdal et al (2006), Sarma et al (2006Sarma et al ( , 2008a, Chen et al (2009Chen et al ( , 2012, Chen and Oliver (2010), Wang et al (2009), Peters et al (2010, Foss and Jensen (2010), Capolei et al (2013), Shirangi and Durlofsky (2015) and Bukshtynov et al (2015). For further references, see Jansen et al (2005Jansen et al ( , 2008Jansen et al ( , 2009) and Hou et al (2015). The potential benefits from the use of CLRM are related to the degree of heterogeneity in the subsurface.…”

Section: Making Use Of Production Data -Closing the Loopmentioning

confidence: 99%

“…In hydrocarbon production 'closed-loop' or 'real-time' approaches have received growing attention as part of various industry initiatives with names as 'smart fields', 'i-fields', 'e-fields', 'integrated operations', 'closed-loop reservoir management' (CLRM), or 'closed-loop field development'; see Jansen et al (2005Jansen et al ( , 2008Jansen et al ( , 2009) and Hou et al (2015) for further references. Independent from these developments, more recently similar concepts were proposed in solid mineral resource extraction (e.g.…”

Section: Introductionmentioning

confidence: 99%

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

Benndorf

2017

Math Geosci

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Advanced data acquisition and process modelling technology provide 'real-time' data and decision support capacity for different aspects of the resource extraction process. Closed-loop approaches have recently been applied to utilize information extracted from these data in combination with advanced computing technology for improved production control in mineral resource extraction. Similar techniques have been developed in the petroleum industry combining computer-assisted model updating with model-based production optimization. This contribution reviews recent developments and methods applied, highlights differences and assesses the potential value added for both application domains. The focus here is on the two main constituents of closed-loop concepts, data assimilation and optimization. Technological readiness of the constituents is assessed, and gaps for further technology development are identified. The value added is illustrated by means of selected cases. Key Wordsclosed-loop reservoir management, real-time mining, data assimilation, optimization Published as Benndorf, J. and Jansen, J.D., 2017: Recent developments in closed-loop approaches for realtime mining and petroleum extraction. Mathematical Geosciences 49 (3) 277-306.

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“…Data assimilation involves modifying the parameters of one or more reservoir models, or the underlying geological models, with the aim to improve their predictive capacity, using measured data from a potentially wide variety of sources such as production data or time-lapse seismics. For further information on CLRM see, e.g., Jansen et al (2005Jansen et al ( , 2008Jansen et al ( , 2009, Naevdal et al (2006), Sarma et al (2008); Chen et al (2009), Wang et al (2009) or Hou et al (2015).…”

Section: Introductionmentioning

confidence: 99%

Clustering Techniques for Value-of-information Assessment in Closed-loop Reservoir Management

Barros

Yap

Insuasty³

et al. 2016

Proceedings

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Closed-loop reservoir management (CLRM) is a combination of life-cycle optimization and computerassisted history matching. The application of the CLRM framework to real field cases can be computationally demanding. An even higher computational load results from procedures to assess the value of information (VOI) in CLRM. Such procedures, which are performed prior to field operation, i.e. during the field development planning (FDP) phase, require extreme amounts of simulations. Therefore, we look for alternatives to reduce this computational cost. In particular we compare various clustering techniques to select a limited number of representative members from an ensemble of reservoir models. Using K-means clustering, multi-dimensional scaling and tensor decomposition techniques, we test the effectiveness of different dissimilarity measures such as distance in parameter space, distance in terms of flow patterns and distance in optimal sets of controls. As a first step towards large-scale application we apply several of these measures to a VOI-CLRM exercise using a simple 2D reservoir model which results in a reduction of the necessary number of forward reservoir simulations from millions to thousands.

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A review of closed-loop reservoir management

Cited by 56 publications

References 135 publications

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

Clustering Techniques for Value-of-information Assessment in Closed-loop Reservoir Management

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