Closed-Loop Feedback Control for Production Optimization of Intelligent Wells Under Uncertainty

Dilib, Fahad Ahmed; Jackson, Matthew D.

doi:10.2118/150096-pa

Cited by 20 publications

(5 citation statements)

References 91 publications

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“…It is a typical reservoir scenario produced by a horizontal well under the drive of strong bottom water pressure, as depicted in Figure 8. This model is a simplified representation of a thin oil reservoir in Indiana, USA (Bryant et al, 2002), and it has been frequently used in smart well production studies (Raghuraman et al, 2003;Bryant et al, 2004;Addiego-Guevara et al, 2008;Dilib and Jackson, 2013 Table 3. Capillary pressure is neglected, whereas wellbore friction is considered.…”

Section: Production Controls Combined With Borehole Radars Reservoir mentioning

confidence: 99%

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

et al. 2018

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The recently developed smart well technology allows for sectionalized production control by means of downhole inflow control valves and monitoring devices. We consider borehole radars as permanently installed downhole sensors to monitor fluid evolution in reservoirs, and it provides the possibility to support a proactive control for smart well production. To investigate the potential of borehole radar on monitoring reservoirs, we establish a 3D numerical model by coupling electromagnetic propagation and multiphase flow modeling in a bottom-water drive reservoir environment. Simulation results indicate that time-lapse downhole radar measurements can capture the evolution of water and oil distributions in the proximity (order of meters) of a production well, and reservoir imaging with an array of downhole radars successfully reconstructs the profile of a flowing water front. With the information of reservoir dynamics, a proactive control procedure with smart well production is conducted. This method observably delays the water breakthrough and extends the water-free recovery period. To assess the potential benefits that borehole radar brings to hydrocarbon recovery, three production strategies are simulated in a thin oil rim reservoir scenario, i.e., a conventional well production, a reactive production, and a combined production supported by borehole radar monitoring. Relative to the reactive strategy, the combined strategy further reduces cumulative water production by 66.89%, 1.75%, and 0.45% whereas it increases cumulative oil production by 4.76%, 0.57%, and 0.31%, in the production periods of 1 year, 5 years, and 10 years, respectively. The quantitative comparisons reflect that the combined production strategy has the capability of accelerating oil production and suppressing water production, especially in the early stage of production. We suggest that borehole radar is a promising reservoir monitoring technology, and it has the potential to improve oil recovery efficiency.

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Section: Production Controls Combined With Borehole Radars Reservoir mentioning

confidence: 99%

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

et al. 2018

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“…ICVs can be employed with two distinct reservoir control strategies, namely: reactive and proactive strategies. In the reactive strategy, ICVs are adjusted according to the existing reservoir and well-operating parameters, including factors such as water cut or gas oil ratio [13][14][15][16][17][18][19][20][21][22]. The proactive strategy, on the other hand, aims to optimize long-term objectives by proactively delaying future water/gas breakthroughs and, in general, optimizing the in-reservoir flood fronts [23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Completion Performance Evaluation in Multilateral Wells Incorporating Single and Multiple Types of Flow Control Devices Using Grey Wolf Optimizer

Ahdeema,

Sefat,

Muradov

et al. 2024

Processes

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There has been a tendency in oil and gas industry towards the adoption of multilateral wells (MLWs) with completions that incorporate multiple types of flow control devices (FCDs). In this completion technique, passive inflow control devices (ICDs) or autonomous inflow control devices (AICDs) are positioned within the laterals, while interval control valves (ICVs) are installed at lateral junctions to regulate the overall flow from each lateral. While the outcomes observed in real field applications appear promising, the efficacy of this specific downhole completion combination has yet to undergo comparative testing against alternative completion methods that employ a singular flow control device type. Additionally, the design and current evaluations of such completions are predominantly based on analytical tools that overlook dynamic reservoir behavior, long-term production impacts, and the correlation effects among different devices. In this study, we explore the potential of integrating various types of flow control devices within multilateral wells, employing dynamic optimization process using numerical reservoir simulator while the Grey Wolf Optimizer (GWO) is used as optimization algorithm. The Egg benchmark reservoir model is utilized and developed with two dual-lateral wells. These wells serve as the foundation for implementing and testing 22 distinct completion cases considering single-type and multiple types of flow control devices under reactive and proactive management strategies. This comprehensive investigation aims to shed light on the advantages and limitations of these innovative completion methods in optimizing well and reservoir performance. Our findings revealed that the incorporation of multiple types of FCDs in multilateral well completions significantly enhance well performance and can surpass single-type completions including ICDs or AICDs. However, this enhancement depends on the type of the device implemented inside the lateral and the control strategy that is used to control the ICVs at the lateral junctions. The best performance of multiple-type FCD-based completion was achieved through combining AICDs with reactive ICVs which achieved around 75 million USD profit. This represents 42% and 22% increase in the objective function compared to single-type ICDs and AICDs installations, respectively. The optimal settings for ICD and AICD in individual applications may significantly differ from the optimal settings when combined with ICVs. This highlights a strong correlation between the different devices (control variables), proving that using either a common, simplified analytical, or a standard sequential optimization approach that do not explore this inter-dependence between devices would result in sub-optimal solutions in such completion cases. Notably, the ICV-based completion, where only ICVs are installed with lateral completion, demonstrated superior performance, particularly when ICVs are reactively controlled, resulting in an impressive 80 million USD NPV which represents 53% and 30% increase in the objective function compared to single-type ICDs and AICDs installations, respectively.

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“…These methods involve coupling a reservoir simulator with an optimization algorithm. Following are some major publications classified based on the employed optimization algorithm: (a) metaheuristic and population-based algorithms [5,[7][8][9][10][11][12][13][14][15][16] (b) gradient-based or derivative-based algorithms [17][18][19][20][21], and (c) stochastically estimated gradient-based algorithms [22][23][24][25].…”

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

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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.

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Closed-Loop Feedback Control for Production Optimization of Intelligent Wells Under Uncertainty

Cited by 20 publications

References 91 publications

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

Completion Performance Evaluation in Multilateral Wells Incorporating Single and Multiple Types of Flow Control Devices Using Grey Wolf Optimizer

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

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