Iterative sequential robust optimization of quantity and location of wells in field development under subsurface, operational and economic uncertainty

Mirzaei‐Paiaman, Abouzar; Santos, Susana M.G.; Schiozer, Denis José

doi:10.1016/j.petrol.2022.111005

Cited by 8 publications

(3 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this work, we used the Iterative Discrete Latin Hypercube (IDLHC) (Hohendorff Filho et al, 2016Botechia et al, 2021). Schiozer (2022) showed four approaches to optimize the control of ICVs in injectors. Here, we follow the approach that resulted in the best economic performance of the goal is to equalize the cumulative injected fluid volume between the zones of the injectors, as .…”

Section: Icvs Of Producersmentioning

confidence: 99%

See 1 more Smart Citation

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

Botechia,

Schiozer

2023

BJPG

View full text Add to dashboard Cite

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.

show abstract

Section: Icvs Of Producersmentioning

confidence: 99%

“…The second way is to perform a robust optimization (Figure 4), in which all RMs are optimized simultaneously (Schiozer et al, 2022;Mirzaei-Paiaman et al, 2022). In this case, only one production strategy is obtained.…”

Section: Part Ii: Probabilistic Proceduresmentioning

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

View full text Add to dashboard Cite

show abstract

“…This complexity arises from the large number of correlated control variables and the computationally demanding objective function [28]. A sequential optimization approach, which involves dividing the problem into subproblems based on the type of control variables and optimizing them sequentially, has been suggested by some researchers to alleviate this issue [29]. However, this approach can lead to a suboptimal solution due to the overlooking of correlation effects between control variables.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Framework for Enhanced Dynamic Optimization of Intelligent Completion Design in Multilateral Wells with Multiple Types of Flow Control Devices

Ahdeema,

Haghighat Sefat,

Muradov

2023

Energies

View full text Add to dashboard Cite

Multilateral wells (MLWs) equipped with multiple flow control devices (FCDs) are becoming increasingly favored within the oil sector due to their ability to enhance well-to-reservoir exposure and effectively handle unwanted fluid breakthrough. However, combining various types of FCDs in multilateral wells poses a complex optimization problem with a large number of highly correlated control variables and a computationally expensive objective function. Consequently, standard optimization algorithms, including metaheuristic and gradient-based approaches, may struggle to identify an optimal solution within a limited computational resource. This paper introduces a novel hybrid optimization (HO) framework combining particle swarm optimization (PSO) and Simultaneous Perturbation Stochastic Approximation (SPSA). It is developed to efficiently optimize the completion design of MLWs with various FCDs while overcoming the individual limitations of each optimization algorithm. The proposed framework is further enhanced by employing surrogate modelling and global sensitivity analysis to identify critical parameters (i.e., highly sensitive) that greatly affect the objective function. This allows for a focused optimization effort on these key parameters, ultimately enhancing global optimization performance. The performance of the novel optimization framework is evaluated using the Olympus benchmark reservoir model. The model is developed by three intelligent dual-lateral wells, with inflow control devices (ICDs) installed within the laterals and interval control valves (ICVs) positioned at the lateral junctions. The results show that the proposed hybrid optimization framework outperforms all industry-standard optimization techniques, achieving a Net Present Value of approximately USD 1.94 billion within a limited simulation budget of 2500 simulation runs. This represents a substantial 26% NPV improvement compared to the open-hole case (USD 1.54 billion NPV). This improvement is attributed to more efficient water breakthrough management, leading to a notable 24% reduction in cumulative water production and, consequently, a 26% increase in cumulative oil production.

show abstract

Analysis of different objective functions in petroleum field development optimization

Rostamian,

de Sousa Miranda,

Mirzaei-Paiaman

et al. 2024

J Petrol Explor Prod Technol

View full text Add to dashboard Cite

Oilfield development optimization plays a vital role in maximizing the potential of hydrocarbon reservoirs. Decision-making in this complex domain can rely on various objective functions, including net present value (NPV), expected monetary value (EMV), cumulative oil production (COP), cumulative gas production (CGP), cumulative water production (CWP), project costs, and risks. However, EMV is often the main function when optimization is performed under uncertainty. The behavior and performance of different objective functions has been investigated in this paper, when EMV is the primary criterion for optimization under reservoir and economic uncertainty. One of the goals of this study is to provide insights into the advantages and limitations of employing EMV as the sole objective function in oil field development decision-making. The designed optimization problem included sequential optimization of design variables including well positions, well quantity, well type, platform capacity, and internal control valve placements. A comparative analysis is presented, contrasting the outcomes obtained from optimizing the EMV-based objective function against traditional objective functions. The study underscores the importance of incorporating multiple objective functions alongside EMV to guide decision-making in oilfield development. Potential benefits in minimizing CGP and CWP are revealed, aiding in the mitigation of environmental impact and optimization of resource utilization. A strong correlation between EMV and COP is identified, highlighting EMV’s role in improving COP and RF.

show abstract

Iterative sequential robust optimization of quantity and location of wells in field development under subsurface, operational and economic uncertainty

Cited by 8 publications

References 60 publications

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

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

Hybrid Framework for Enhanced Dynamic Optimization of Intelligent Completion Design in Multilateral Wells with Multiple Types of Flow Control Devices

Analysis of different objective functions in petroleum field development optimization

Contact Info

Product

Resources

About