Abstract
Decisions regarding problem conceptualization, search approach, and how best to parametrize optimization methods for practical application are key to successful implementation of optimization approaches within georesources field development projects. This work provides decision support regarding the application of derivative-free search approaches for concurrent optimization of inflow control valves (ICVs) and well controls. A set of state-of-the-art approaches possessing different search features is implemented over two reference cases, and their performance, resource requirements, and specific method configurations are compared across multiple problem formulations for completion design. In this study, problem formulations to optimize completion design comprise fixed ICVs and piecewise-constant well controls. The design is optimized by several derivative-free methodologies relying on parallel pattern-search (tAPPS), population-based stochastic sampling (tPSO) and trust-region interpolation-based models (tDFTR). These methodologies are tested on a heterogeneous two-dimensional case and on a realistic case based on a section of the Olympus benchmark model. Three problem formulations are applied in both cases, i.e., one formulation optimizes ICV settings only, while two joint configurations also treat producer and injector controls as variables. Various method parametrizations across the range of cases and problem formulations exploit the different search features to improve convergence, achieve final objectives and infer response surface features. The scope of this particular study treats only deterministic problem formulations. Results outline performance trade-offs between parallelizable algorithms (tAPPS, tPSO) with high total runtime search efficiency and the local-search trust-region approach (tDFTR) providing effective objective gains for a low number of cost function evaluations. tAPPS demonstrates robust performance across different problem formulations that can support exploration efforts, e.g., during a pre-drill design phase while multiple independent tDFTR runs can provide local tuning capability around established solutions in a time-constrained post-drill setting. Additional remarks regarding joint completion design optimization, comparison metrics, and relative algorithm performance given the varying problem formulations are also made.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
Data Availability
The optimization code used in this project is available on the GitHub page of the Petroleum Cybernetics Group NTNU (https://github.com/PetroleumCyberneticsGroup/FieldOpt-Research-Open). The data supporting this study’s findings are available from the corresponding author upon reasonable request.
References
Constable, M.V., Antonsen, F., Stalheim, S.O., Olsen, P.A., Fjell, Ø.Z., Dray, N., Eikenes, S., Aarflot, H., Haldorsen, K., Digranes, G., Seydoux, J., Omeragic, D., Thiel, M., Davydychev, A., Denichou, J.M., Salim, D., Frey, M., Homan, D., Tan, S.: Looking ahead of the bit while drilling: From vision to reality. SPWLA 57th Annual Logging Symposium (2016). SPWLA-2016-MMMM
Bergmo, P.E.S., Grimstad, A.A.: Water Shutoff Technologies for Reduced Energy Consumption. SPE Norway Subsurface Conference (2022). https://doi.org/10.2118/209555-MS. SPE-209555-MS
Leung, E., Nukhaev, M., Gottumukkala, V., Samosir, H., El-Fattah, M.A., Ogunsanwo, O., Gonzalez, A.: Horizontal well placement and completion optimisation in carbonate reservoirs. SPE Caspian Carbonates Technology Conference p. 19 (2010). https://doi.org/10.2118/140048-MS. SPE-140048-MS
Krogstad, S., Nilsen, H.M.: Efficient adjoint-based well-placement optimization using flow diagnostics proxies. ECMOR XVII - 17th European Conference on the Mathematics of Oil Recovery, Online Event (2020). https://doi.org/10.3997/2214-4609.202035227
Volkov, O., Voskov, D.V.: Effect of time stepping strategy on adjoint-based production optimization. Comput. Geosci. 20(3), 707–722 (2016). https://doi.org/10.1007/s10596-015-9528-1
Al-Khelaiwi, F.T., Birchenko, V.M., Konopczynski, M.R., Davies, D.R.: Advanced wells: A comprehensive approach to the selection between passive and active inflow-control completions. SPE Prod. Oper. 25(03), 305–326 (2010). https://doi.org/10.2118/132976-PA. SPE-132976-PA
Todman, S., Wood, G., Jackson, M.D.: Modelling and optimizing inflow control devices. SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition p. 19 (2017). SPE-188012-MS
van der Bol, L., McCarty, A., Pritchett, J., Sripornprasert, Y., Goh, G., Ridho, M., Natapak, R., Sowmyanarayanan, N.M.: ICD design optimisation with single-well dynamic 3D modelling and real-time operation support. International Petroleum Technology Conference p. 16 (2016). https://doi.org/10.2523/IPTC-18848-MS. IPTC-18848-MS
Holmes, J.A.: Modeling advanced wells in reservoir simulation. J. Pet. Technol. 53, 54–66 (2001). https://doi.org/10.2118/72493-JPT. SPE-72493-JPT
Gurses, S.F., Vasper, A.C.: Optimized modeling workflows for designing passive flow control devices in horizontal wells. SPE Reservoir Characterization and Simulation Conference and Exhibition p. 10 (2013). https://doi.org/10.2118/166052-MS. SPE-166052-MS
Jesmani, M., Jafarpour, B., Bellout, M.C., Foss, B.: A reduced random sampling strategy for fast robust well placement optimization. J. Petrol. Sci. Eng. 184, 106414 (2020). https://doi.org/10.1016/j.petrol.2019.106414
Holmes, J.A., Barkve, T., Lund, O.: Application of a multisegment well model to simulate flow in advanced wells. SPE European Petroleum Conference pp. 171–181 (1998). https://doi.org/10.2118/50646-MS. SPE-50646-MS
Youngs, B., Neylon, K.J., Holmes, J.A.: Recent advances in modeling well inflow control devices in reservoir simulation. International Petroleum Technology Conference p. 6 (2009). IPTC-13925-MS
Maas, T.R., Bouts, M.N., Joosten, G.J., Jansen, J.D.: The impact of smart completions on optimal well trajectories. Abu Dhabi International Petroleum Exhibition publisher & Conference (2017). https://doi.org/10.2118/188368-MS. SPE-188368-MS
Gurses, S., Chochua, G., Rudic, A., Kumar, A.: Dynamic modeling and design optimization of cyclonic autonomous inflow control devices. SPE Reservoir Simulation Conference p. 15 (2019). https://doi.org/10.2118/193824-MS. SPE-193824-MS
Youngs, B., Neylon, K., Holmes, J.: Multisegment well modeling optimizes inflow control devices. World Oil pp. 37–42 (2010)
Agrawal, A., Leeuwen, P.V., Demirbas, B., Hajj, J.: Surface management of gas breakthrough in thin oil rim waxy reservoir: A case study. SPE Intelligent Energy International Conference and Exhibition p. 25 (2016). https://doi.org/10.2118/181077-MS. SPE-181077-MS
Fernandes, P., Li, Z., Zhu, D.: Understanding the roles of inflow-control devices in optimizing horizontal-well performance. SPE Annual Technical Conference and Exhibition p. 12 (2009). https://doi.org/10.2118/124677-MS. SPE-124677-MS
Webb, S.J., Revus, D., Myhre, A.M., Goodwin, N.H., Dunlop, N., Heritage, J.: Rapid model updating with right-time data - ensuring models remain evergreen for improved reservoir management. Intelligent Energy Conference and Exhibition p. 13 (2008). https://doi.org/10.2118/112246-MS. SPE-112246-MS
Antonsen, F., Teixeira De Oliveira, M.E., Petersen, S.A., Metcalfe, R.W., Hermanrud, K., Constable, M.V., Boyle, C.T., Eliassen, H.E., Salim, D., Seydoux, J., Omeragic, D., Thiel, M., Denichou, J.M., Etchebes, M., Nickel, M.: Geosteering in complex mature fields through integration of 3D multi-scale LWD-data, geomodels, surface and time-lapse seismic. SPWLA 59th Annual Logging Symposium p. 16 (2018). SPWLA-2018-Q
Warrlich, G.M.D., Abu-Shiekah, I., Alexander, D.M., Zhu, F., Goossens, P.M., Tull, S.S., Al-Lamki, A.A.: Maintaining an “Evergreen” model to optimise a waterflood development in a carbonate transition zone field. SPE/EAGE Reservoir Characterization and Simulation Conference p. 14 (2009). https://doi.org/10.2118/125552-MS. SPE-125552-MS
Salim, D., Couto, P., Alves, J., Freitas, E., Haq, S., Denichou, J.M.: Optimizing recovery by integrating an advanced reservoir simulation approach into the drilling of horizontal wells. Offshore Technology Conference (2015). OTC-26161-MS
Jesmani, M., Bellout, M.C., Hanea, R., Foss, B.: Well placement optimization subject to realistic field development constraints. Comput. Geosci. 20(6), 1185–1209 (2016). https://doi.org/10.1007/s10596-016-9584-1
Goh, G., Tan, T., Zhang, L.M.: A unique ICD’s advance completions design solution with single well dynamic modeling. IADC/SPE Asia Pacific Drilling Technology Conference p. 12 (2016). https://doi.org/10.2118/180672-MS. SPE-180672-MS
Dong, C., Dupuis, C., Morriss, C., Legendre, E., Mirto, E., Kutiev, G., Denichou, J.M., Viandante, M., Seydoux, J., Bennett, N., Zhu, Q., Zhong, X.: Application of automatic stochastic inversion for multilayer reservoir mapping while drilling measurements. Abu Dhabi International Petroleum Exhibition and Conference p. 14 (2015). https://doi.org/10.2118/177883-MS. SPE-177883-MS
Seydoux, J., Legendre, E., Mirto, E., Dupuis, C., Denichou, J.M., Bennett, N., Kutiev, G., Kuchenbecker, M., Morriss, C., Yang, L.: Full 3D deep directional resistivity measurements optimize well placement and provide reservoir-scale imaging while drilling. SPWLA 55th Annual Logging Symposium p. 14 (2014). SPWLA-2014-LLLL
Maggs, D., Raffn, A.G., Porturas, F., Murison, J., Tay, F., Suwarlan, W., Samsudin, N.B., Yusmar, W.Z.A., Yusof, B.W., Imran, T.N.O.M., Abdullah, N.A., Reffin, M.Z.B.M.: Production optimization for second stage field development using ICD and advanced well placement technology. Europec/EAGE Conference and Exhibition p. 11 (2008). https://doi.org/10.2118/113577-MS. SPE-113577-MS
Henriksen, K.H., Gule, E.I., Augustine, J.R.: Case study: The application of inflow control devices in the Troll field. SPE Europec/EAGE Annual Conference and Exhibition p. 5 (2006). https://doi.org/10.2118/100308-MS. SPE-100308-MS
Montaron, B.A., Bradley, D.C., Cooke, A., Prouvost, L.P., Raffn, A.G., Vidal, A., Wilt, M.: Shapes of flood fronts in heterogeneous reservoirs and oil recovery strategies. SPE/EAGE Reservoir Characterization and Simulation Conference p. 18 (2007). https://doi.org/10.2118/111147-MS. SPE-111147-MS
Raffn, A.G., Zeybek, M., Moen, T., Lauritzen, J.E., Sunbul, A.H., Hembling, D.E., Majdpour, A.: Case histories of improved horizontal well cleanup and sweep efficiency with nozzle based inflow control devices (ICD) in sandstone and carbonate reservoirs. Offshore Technology Conference p. 9 (2008). https://doi.org/10.4043/19172-MS. OTC-19172-MS
Karim, R.A., Goh, K.F.G., Nuriyadi, M.A., Ahmad, N.A., Leung, E., Murison, J.A.: Horizontal well optimization with inflow control devices (ICDs) application in heterogeneous and dipping gas-capped oil reservoirs. SPE Annual Technical Conference and Exhibition p. 15 (2010). https://doi.org/10.2118/133336-MS. SPE-133336-MS
Venkitaraman, A., Manrique, J.F., Poe, B.D.J.: A comprehensive approach to completion optimization. SPE Eastern Regional Meeting p. 11 (2001). SPE-72386-MS
Al Hashemi, M., Bellah, S., Gurses, S., Akhtar, M.N.: ICD completions optimization for an offshore Abu Dhabi well using dynamic modeling. SPE Reservoir Characterization and Simulation Conference and Exhibition p. 9 (2013). https://doi.org/10.2118/165962-MS. SPE-165962-MS
Li, D., Alobedli, A., Selvam, B., Azoug, Y., Obeta, C., Nguyen, M., Al-Shehhi, B.H.: A new ICD/ICV well completion design optimizer and well management logic for full field reservoir simulation with multiple ICD/ICV wells. Abu Dhabi International Petroleum Exhibition publisher & Conference p. 17 (2017). https://doi.org/10.2118/188642-MS. SPE-188642-MS
Holmes, J.A., Byer, T.J., Edwards, D.A., Stone, T.W., Pallister, I., Shaw, G.J., Walsh, D.: A unified wellbore model for reservoir simulation. SPE Annual Technical Conference and Exhibition p. 14 (2010). https://doi.org/10.2118/134928-MS. SPE-134928-MS
Stone, T.W., Bennett, J., Law, D.H.S., Holmes, J.A.: Thermal simulation with multisegment wells. SPE Reserv. Eval. Eng. 5(03), 206–218 (2002). https://doi.org/10.2118/78131-PA. SPE-78131-PA
Elfeel, M.A., Goh, G., Biniwale, S.: Advanced completion optimization ACO: A comprehensive workflow for flow control devices (2021). https://doi.org/10.2523/IPTC-21189-MS. IPTC-21189-MS
Volkov, O., Bellout, M.C.: Gradient-based constrained well placement optimization. J. Petrol. Sci. Eng. 171, 1052–1066 (2018). https://doi.org/10.1016/j.petrol.2018.08.033
Volkov, O., Bellout, M.C.: Gradient-based production optimization with simulation-based economic constraints. Comput. Geosci. 21(5), 1385–1402 (2017). https://doi.org/10.1007/s10596-017-9634-3
Baumann, E.J.M., Dale, S.I., Bellout, M.C.: FieldOpt: A powerful and effective programming framework tailored for field development optimization. Comput. Geosci. 135, 104379 (2020). https://doi.org/10.1016/j.cageo.2019.104379
FieldOpt Research: Open-source repository with up-to-date research code. https://github.com/PetroleumCyberneticsGroup/FieldOpt-Research-Open (2022). Accessed 14 Aug 2022
Kristoffersen, B.S., Bellout, M.C., Silva, T.L., Berg, C.F.: An automatic well planner for complex well trajectories. Math. Geosci. 53(8), 1881–1905 (2021). https://doi.org/10.1007/s11004-021-09953-x
Silva, T.L., Bellout, M.C., Giuliani, C., Camponogara, E., Pavlov, A.: A derivative-free trust-region algorithm for well control optimization. ECMOR XVII - 17th European Conference on the Mathematics of Oil Recovery, Online Event (2020). https://doi.org/10.3997/2214-4609.202035086
Silva, T.L., Bellout, M.C., Giuliani, C., Camponogara, E., Pavlov, A.: Derivative-free trust region optimization for robust well control under geological uncertainty. Comput. Geosci. 26(2), 329–349 (2022). https://doi.org/10.1007/s10596-022-10132-y
Isebor, O.J., Durlofsky, L.J., Echeverría Ciaurri, D.: A derivative-free methodology with local and global search for the constrained joint optimization of well locations and controls. Comput. Geosci. 18(3–4), 463–482 (2014). https://doi.org/10.1007/s10596-013-9383-x
Hough, P.D., Kolda, T.G., Torczon, V.J.: Asynchronous parallel pattern search for nonlinear optimization. SIAM J. Sci. Comput. 23(1), 134–156 (2001)
Kolda, T.G.: Revisiting asynchronous parallel pattern search for nonlinear optimization. SIAM J. Optim. 16(2), 563–586 (2005)
Conn, A., Scheinberg, K., Vicente, L.: Introduction to derivative-free optimization. Society for Industrial and Applied Mathematics (2009). https://doi.org/10.1137/1.9780898718768
Charles, A., Dennis, J.E.: Mesh adaptive direct search algorithms for constrained optimization. SIAM J. Optim. 17(1), 188–217 (2006). https://doi.org/10.1137/040603371
Tamara, K.G., Virginia, T.: Understanding asynchronous parallel pattern search. Tech. rep., Livermore, CA (2002)
Floreano, D., Mattiussi, C.: Bio-Inspired Artificial Intelligence: Theories, Methods and Technologies. MIT Press (2008)
Gad, A.G.: Particle swarm optimization algorithm and its applications: A systematic review. Arch. Comput. Meth. Eng. pp. 1–31 (2022)
Forouzanfar, F., Reynolds, A.C., Li, G.: Optimization of the well locations and completions for vertical and horizontal wells using a derivative-free optimization algorithm. J. Pet. Sci. Eng. 86-87(Supplement C), 272–288 (2012). https://doi.org/10.1016/j.petrol.2012.03.014
Merlini Giuliani, C.: Distributed Derivative Free Optimization. Universidade Federal de Santa Catarina, Presentation PhD Defense (2016)
Audet, C., Hare, W.: Derivative-free and blackbox optimization. Springer (2017)
Gill, P.E., Murray, W., Saunders, M.A.: SNOPT: An SQP algorithm for large-scale constrained optimization. SIAM Rev. 47(1), 99–131 (2005). https://doi.org/10.1137/S0036144504446096
Conn, A.R., Scheinberg, K., Vicente, L.N.: Geometry of sample sets in derivative-free optimization: Polynomial regression and underdetermined interpolation. IMA J. Numer. Anal. 28(4), 721 (2008). https://doi.org/10.1093/imanum/drn046
Conn, A.R., Scheinberg, K., Vicente, L.N.: Geometry of interpolation sets in derivative free optimization. Math. Program. 111(1), 141–172 (2008). https://doi.org/10.1007/s10107-006-0073-5
Conn, A., Gould, N., Toint, P.: Trust region methods. Society for Industrial and Applied Mathematics (2000). https://doi.org/10.1137/1.9780898719857
Scheinberg, K., Toint, P.L.: Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization. SIAM J. Optim. 20(6), 3512–3532 (2010)
Christie, M.A., Blunt, M.J.: Tenth SPE comparative solution project: A comparison of upscaling techniques. SPE Reserv. Eval. Eng. 4(4), 308–317 (2001). https://doi.org/10.2118/72469-PA
Fonseca, R., Della Rossa, E., Emerick, A., Hanea, R., Jansen, J.: Overview of the Olympus field development optimization challenge. ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery 2018(1), 1–10 (2018). https://doi.org/10.3997/2214-4609.201802246
Bellout, M.C., Echeverría Ciaurri, D., Durlofsky, L.J., Foss, B., Kleppe, J.: Joint optimization of oil well placement and controls. Comput. Geosci. 16(4), 1061–1079 (2012). https://doi.org/10.1007/s10596-012-9303-5
Gill, P.E., Murray, W., Saunders, M.A.: Practical Optimization. Academic Press, San Diego, CA, USA (1981)
Acknowledgements
The authors would like to thank Jarle Haukås for valuable contributions to the framing of this research, and SLB Stavanger Research (SSR) for hosting the authors during parts of this research.
Funding
Open access funding provided by NTNU Norwegian University of Science and Technology (incl St. Olavs Hospital - Trondheim University Hospital).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Bellout, M.C., Silva, T.L., Bakke, J.Ø.H. et al. Derivative-free search approaches for optimization of well inflow control valves and controls. Comput Geosci 28, 431–459 (2024). https://doi.org/10.1007/s10596-024-10270-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10596-024-10270-5