Day 2 Wed, January 25, 2023最新文献

{"title":"The Sabriyah Mauddud Dynamic Model Rebuild – Tackling the History Match of a Giant and Complex Carbonate Reservoir Through a Tailored-Made Sector-Centered History Match Approach","authors":"E. Hernandez, S. Boekhout, G. V. van Essen, B.-R. de Zwart, N. Al-Sultan, B. Al-Otaibi, Adrian Crawford, M. Obermaier, B. Dewever","doi":"10.2118/212586-ms","DOIUrl":"https://doi.org/10.2118/212586-ms","url":null,"abstract":"\u0000 This work presents the application of a fit-for-purpose history match workflow to a giant and geologically complex carbonate reservoir with over 60 years of production/injection history and 600+ wells. The target was to deliver, within schedule and spec, a high-quality sizeable model (15+ million grid blocks) that honored the underlying geologic characteristics and reproduced the distinctive production mechanisms present across the different regions of the reservoir, while keeping parametrization of uncertainties at a manageable level.\u0000 Practical implementation routes were applied to efficiently translate key reservoir plumbing elements and other identified subsurface uncertainties into dynamic modeling components that could be investigated over large uncertainty ranges via Assisted History Matching (AHM) tools.\u0000 To manage the history match process of this vast and mature reservoir, a sophisticated and custom-tailored sector-centered modeling scheme was adopted based on a \"Divide & Conquer\" approach. This tactic divides the big history match problem into smaller more manageable pieces, allowing for simultaneous history match of different sectors by different engineers while having frequent reassembling of sectors into a full-field model to ensure alignment, preserve consistent reservoir behaviors, and update (flux) boundary conditions.\u0000 The iterative sector-based history match scheme applied to the giant field dynamic model made it possible to achieve a good history match within the given time and IT resources available to carry out the history match. The new dynamic model respects the conceptual understanding of the reservoir behavior and honors the available subsurface and production data of approximately 80% of the individual wells within the desired history match criteria.\u0000 The use of the sector modeling workflow approach in a large full field model, allowed for faster turnaround of results for history matching purposes. The applied workflow also demonstrated that achieving a good history match in the individual sectors also resulted in a good history match for the full field model, achieved in a faster way.\u0000 The final model respects the conceptual understanding of reservoir behavior as well as honors the available performance data at a scale which allows not only more reliable production forecasts but also model-based pattern-level waterflood optimization and its use for well location optimization (WLO) studies. The model supports development planning and reservoir management decisions (20+ new wells drilled annually), with waterflooding aiming to increase ultimate recovery by more than 20%.\u0000 The methodology allowed significant time-savings to deliver the dynamic model within a relatively short schedule (~9 months) and required quality specifications. The successful application of the custom-made history match workflow is currently being replicated in other reservoirs of similar scale and complexity in North Kuwait and could also be applie","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131295318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing Oil Recovery Using a Chemical Application in Offshore Environment-Case Study","authors":"A. Khanifar, Arif Azhan Abdul Manap","doi":"10.2118/212618-ms","DOIUrl":"https://doi.org/10.2118/212618-ms","url":null,"abstract":"\u0000 Chemical injection has been identified as one of the upstream strategies by PETRONAS for maximizing oil recovery from a Malaysian offshore oil field which is currently operating under waterflooding and declining in oil production. A chemical application roadmap from laboratory to full field scale was established with numerous technical evaluation stages. The recipe and formulation for this chemical injection were obtained from inclusive laboratory experiments studies including chemical screening, fluid-fluid, and fluid-rock evaluations.\u0000 Pilot field trial tests by single well chemical tracer (SWCT) technique were designed and executed to validate the laboratory results, chemical injection response, and to obtain an operating experience prior full field scale implementation. A simulation modelling study was carried out to obtain a scheme of injection, proper wells pattern, and amount of incremental oil recovery expected from this application. Moreover, an integration study from subsurface to surface including reservoirs, wells, and surface facilities were conducted to find an appropriate development concept and reduce the overall project costs for ensuring being a techno-commercially viable project.\u0000 Laboratory results verifies that a chemical injection consist of 1.0 wt. % alkali and 0.075 wt. % surfactant in an optimum salinity range of 5,000-10,000 ppm and adsorption of 0.30 mg/gr-of-rock should establish an ultralow IFT of 0.001 dyne/cm system and result in 50-75 % Sorw reduction. Favorable results achieve from pilot testes where successfully mobilized substantial amounts of Sor and chemicals easily mixed with no injection problems encountered. They were consistent with laboratory findings and validated a 50-80 % Sorw reduction. Minimum residual oil saturation of 0.06 and 0.08 were seen after chemical application. Soft-water buffers were planned to minimize competing reaction of alkali and allow surfactant to work in more favorable lower salinity water and fortunately, results show that it was not severe enough to prevent the AS system from working. The contrast of initial waterflooding Sor after first pilot completion in two wells indicate an increase of 0.04 in Sorw (0.16 to 0.20 and 0.27 to 0.31) which, interestingly it could be due to a shift in rock wettability toward more water wet system. Modelling study shows a four-year plan including three-year of AS slug and six-month of pre and post buffers is an optimum injection scheme.\u0000 This paper presents an outlook of the chemical project. This knowledge is extremely useful in guiding future laboratory studies and field implementation. Although, chemical was verified technically but significant efforts were made to gauge the development concept with harsh offshore environment, large well spacing, and chemical handling. This study can be used as a technical reference address various challenges that are often encountered in implementing chemical EOR, particularly at an offshore environment.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124839023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vertical Composition Variation with Multiple Samples for Reservoir Model Initialization","authors":"Nour El Droubi, S. Tahir, K. Ghorayeb, Shi Su, Georges Assaf, Samat Ramatullayev, C. Kloucha, Hussein Mustapha","doi":"10.2118/212643-ms","DOIUrl":"https://doi.org/10.2118/212643-ms","url":null,"abstract":"\u0000 A challenging step in reservoir modeling is capturing fluid composition variation. This is a complex task as fluid samples taken from wells in different areas of the reservoir usually have large areal and vertical compositional variation. Modeling representative composition variation with depth in the presence of multiple samples is critical for reservoir simulation and hydrocarbon initially in place assessment, and, on the other hand, a technically challenging task. In this paper, we present an automated workflow integrated in a commercial exploration and production (E&P) software that addresses compositional variation for reservoir simulation model initialization for multiple fluid samples.\u0000 Composition variation with depth requires a depth window, number of depth points, composition, temperature, pressure and reference depth for all fluid samples. Using a specific equation of state (EoS), the workflow is executed for every fluid sample by performing compositional variation with depth based on Gibbs conditions for thermodynamic equilibrium. The output of this step is a composition variation with depth distribution for every fluid sample. Finally, the best-matching model is chosen by comparing each model results with the data for all existing fluid samples.\u0000 The proposed workflow was tested using a specific EoS in a reservoir with several fluid samples. One composition variation with depth model was generated for every fluid sample. In the next step, all models were evaluated by calculating the average errors between the model and each fluid sample. Finally, the best-matching models were selected, and the results were evaluated. It was observed that the best-matching models were able to accurately predict the pressure and saturation pressure for large number of fluid samples. The proposed workflow was also integrated into an industry-leading E&P modeling software platform to serve as an automated functionality that outputs the required files to perform initialization with equilibration of the dynamic reservoir model.\u0000 Capturing fluid composition variation in the reservoir is an important step in reservoir modeling. The proposed work presents an automated workflow that generates the best-matching composition variation with depth model for multiple samples. Using traditional approaches, this is a challenging and time-consuming step as fluid samples taken from wells in different areas of a reservoir can have significant areal compositional variation.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124388073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Effective Approach to Modeling Hydraulic Fracture in a Coarse Scale Simulation Model","authors":"Adan Hanniel Tello Gomez, A. Fekkane, J. Oluwa, Adel Al-Qahtani","doi":"10.2118/212603-ms","DOIUrl":"https://doi.org/10.2118/212603-ms","url":null,"abstract":"\u0000 The use of hydraulic fracturing to improve well productivity in tight reservoirs and connecting unconsolidated quality reservoirs via hydraulic fracturing is very well practiced in the oil industry. Currently to model hydraulic fracture in order to fully assess its effect in the well and its interaction with the formation (or different layers) requires upscaling methods to reach higher resolution (refinement) in order to reach certain accuracy in simulations like sector-based or local grid refinement techniques around well-reservoir modeling. However, modeling hydraulic fracturing in a large full-field reservoir simulation model with hundreds of wells and millions of cells is computationally very expensive. The aim of this proposal is to provide an alternative modeling of hydraulic fracturing at any size-based cell without the need of refinement saving computational cost.\u0000 Even though computational capacity has increase exponentially in the last decade, the complexity and resolution of simulation models does overwhelm conventional computational processing leaving high resolutions models to corporations and companies with major resources in computing as the only capable to ensure an effective simulation of stimulation in wells modeling interaction with full field reservoir models. The search of alternatives to simplify and propose representative models of hydraulic fracture is part of needed applications to provide tools in field development and reservoir management scenarios, specially if a sizable data base with good quality surveying and compensated with production and performance data can represent key cornerstones to create meaningful characteristic variables in order to apply in modeling and forecast activities as history matching.\u0000 This paper proposes a new approach to model the hydraulic fracturing (HF) effect based on a volumetric relation between created fracture and influenced volume in a designated reservoir/productive formation to be use specially in coarse simulation models to simulate the enhancement of the hydraulic fracture effects in production and history matching modeling. The use of field data and pressure matched properties based on stimulation parameters is the foundation to rely on. The new approach helped developing a fracture factor used to model permeability interaction between formation and stimulated volume designated by cell size and position. The proposed approach guaranties no change on regional nor alteration of static model properties maintaining the geological concept intact and providing a more realistic approach in order to simulate effectively stimulation in modeled wells in any type of grid or geometry of cells.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116730787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}