Ensemble-Based Multi-Objective Optimization of On-Off Control Devices Under Geological Uncertainty

Fonseca, R.M.; Leeuwenburgh, O.; Rossa, Ernesto Della; Hof, Paul M.J. Van den

doi:10.2118/173268-ms

Cited by 13 publications

(3 citation statements)

References 21 publications

(55 reference statements)

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“…Most conventional horizontal well design and fracturing optimization methods focus on finding the optimal design parameters to specific metrics, such as estimated ultimate recovery (EUR), cumulative gas production over a while, or net present value (NPV). − The economic analysis recommends the decision with maximum NPV (present value of net benefits, or benefits minus costs, over time) or maximum benefit–cost ratio (present value of benefits to present value of fees). The NPV is calculated to obtain the present value of future income generated by eliminating the use of standard economic techniques.…”

Section: Constructing Integrated Optimization Modelmentioning

confidence: 99%

Novel Self-Adaptive Shale Gas Production Proxy Model and Its Practical Application

Qiao

Wang

et al. 2022

ACS Omega

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Recently, production optimization has gained increasing interest in the petroleum industry. The most computationally intensive and critical part of the production optimization process is the evaluation of the production function performed by the numerical reservoir simulator. Employing proxy models as a substitute for the reservoir simulator is proposed for alleviating this high computational cost. In this study, a new approach to construct adaptive proxy models for production optimization problems is proposed. An adaptive difference evolution algorithm (SaDE) optimized least-squares support vector machine (LSSVM) is used as an approximation function, while training is performed using a self-adaptive response surface experimental design (SaRSE). SaDE selects the optimal hyperparameters of LSSVM during the training process to improve the prediction accuracy of the proxy model. Cross-validation methods are used in the recursive training and network evaluation phases. The developed method is used to optimize the production of block gas reservoir models. Computational results confirm that the developed adaptive proxy model outperforms traditional regression methods. It is further verified that when the experimental data are updated, the alternative model still has high prediction accuracy when performing the objective function evaluation. The results show that the proposed proxy modeling approach enhances the entire optimization process by providing a fast approximation of the actual reservoir simulation model with better accuracy.

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Section: Constructing Integrated Optimization Modelmentioning

confidence: 99%

Novel Self-Adaptive Shale Gas Production Proxy Model and Its Practical Application

Qiao

Wang

et al. 2022

ACS Omega

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“…In order to design a production strategy to account for parametric uncertainties in reservoir models, Robust Optimization (RO) has been applied, see Van Essen et al (2009), Chen et al (2012, Yasari et al (2013) and Fonseca et al (2015). In order to design a production strategy to account for parametric uncertainties in reservoir models, Robust Optimization (RO) has been applied, see Van Essen et al (2009), Chen et al (2012, Yasari et al (2013) and Fonseca et al (2015).…”

Section: Robust Optimizationmentioning

confidence: 99%

Spatial-Temporal Tensor Decompositions for Characterizing Control-Relevant Flow Profiles in Reservoir Models

Moreno¹,

Hof²,

Weiland³

2015

SPE Reservoir Simulation Symposium

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This paper considers the use of spatial-temporal (tensor) decompositions for the compact representations of saturation patterns in reservoir models. Reservoir flow patterns, in the sense of evolution of saturation patterns over time, can be considered to drive the economic performance of reservoirs as they drive the ultimate recovery. This makes the reservoir flow pattern a natural dissimilarity measure between models in the context of production optimization. We show that the application of multilinear algebra techniques allows the construction of low-complexity representations of the essential saturation patterns. The reservoir flow patterns are stored in large-scale multidimensional arrays, and tensor decompositions can be effectively used to describe the spatial-temporal behavior of the reservoir flow patterns. The dimensionality of the reservoir flow patterns can be substantially reduced, showing that a small number of spatial-temporal basis functions are required to characterize the dominant features. When applying the tensor decompositions to flow profiles of an ensemble of realizations they can be used for clustering models with similar dynamical properties, by allowing a fast calculation of a flow-relevant dissimilarity measure between realizations. For large ensembles of realizations they can lead to considerable computational advantages in (robust) optimization. This is illustrated by using a gradient-based technique to maximize Net Present Value (NPV) in water flooding for an ensemble of realizations. Besides in reducing ensemble sizes the resulting tools have potential use in constructing reduced order models.

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“…This operation is dependent on many factors, such as well pattern and reservoir characteristics, which may vary over time (Brouwer & Jansen, 2004;Addiego-Guevara et al, 2008;Pinto et al, 2015). Many studies address optimization procedures for ICV operation (Yeten et al, 2004;Sarma et al, 2005;Naus et al, 2006;Dilib et al 2015;Fonseca et al 2015;Chen & Reynolds, 2017;Ilamah & Waterhouse 2018;Aljubran & Horne, 2019), while some authors also reported real case applications (Emerick & Portella, 2007;Van Essen et al, 2009). Botechia et al (2021) and Botechia and Schiozer (2022) proposed and evaluated different model-based methodologies to optimize the operation of ICVs in producers and injectors, respectively, to improve the management and economic return of fields with the aforementioned characteristics.…”

Section: Introductionmentioning

confidence: 99%

MODEL-BASED OPTIMIZATION OF ICVs’ CONTROL FOR PRODUCERS, INJECTORS, AND WAG-CO2 CYCLES SIZE IN A CARBONATE RESERVOIR UNDER UNCERTAINTY

Botechia,

Schiozer

2023

BJPG

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Life cycle management of oil fields involves complex decisions, with many variables to be considered. In some fields of the Brazilian pre-salt, this task is even more challenging given the ultra-deep water location, with an expressive amount of gas (including CO2) production. This feature becomes a restricting factor for oil production in these types of fields, and a proper management is essential to overcome this issue, improving both production and economic returns. Therefore, Water-Alternate-Gas (WAG) is often used as an Enhanced Oil Recovery- EOR mechanism, providing a better mobility control, improving reservoir sweep and oil recovery. Moreover, WAG can be an alternative for recycling the produced gas, providing an adequate destination (mainly for CO2) and avoiding environmental problems. In this case, we name the method as WAG-CO2. Moreover, Interval Control Valves (ICVs) are also a good alternative to deal with these fields, since they work as flow control devices and allow for a better balance of the fluid flow in the reservoir. In this work, we evaluate the impact of the use of ICVs in producers, injectors, along with WAG cycles size to improve the performance of a developed field. The work consists of two parts. In Part I, using a single simulation model, we performed (1) six hierarchical optimization approaches to verify if the order in which the optimization occurs influences the final results, and (2) a joint optimization of all parameters for comparison purposes. The final strategies are simulated in a reference case (representing the “true response” of the field) to evaluate how the achieved control rules would behave in a real field. In Part II, we considered a probabilistic procedure, applying one of the hierarchical approaches in several representative models (RMs) expressing uncertain scenarios. In this case, we compared nominal optimization of individual RMs against a robust optimization (in which all RMs are optimized simultaneously). The study is applied to the benchmark case SEC1_2022, a synthetic model analogous to a pre-salt field. The results show an expressive increase in the economic return of the field with a proper operation of the ICVs and size of the WAG-CO2 cycles, despite the platform being restricted by gas production capacity. This result occurred because of a better balance in fluid flow through the reservoir and among wells. Moreover, in the first part of the work, all hierarchical approaches presented very similar results in terms of NPV, so the order of the optimization steps did not significantly affect the results. The non-hierarchical approach presented a slightly better result, but still close to those obtained in the hierarchical approaches. Furthermore, the most impacting variable was the ICV for producers, followed by ICV for injectors and, then, WAG-CO2 cycles. Similar tendencies were observed in the second part of the work, with higher expected economic return for the robust optimization.

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Ensemble-Based Multi-Objective Optimization of On-Off Control Devices Under Geological Uncertainty

Cited by 13 publications

References 21 publications

Novel Self-Adaptive Shale Gas Production Proxy Model and Its Practical Application

Novel Self-Adaptive Shale Gas Production Proxy Model and Its Practical Application

Spatial-Temporal Tensor Decompositions for Characterizing Control-Relevant Flow Profiles in Reservoir Models

MODEL-BASED OPTIMIZATION OF ICVs’ CONTROL FOR PRODUCERS, INJECTORS, AND WAG-CO2 CYCLES SIZE IN A CARBONATE RESERVOIR UNDER UNCERTAINTY

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