Day 2 Wed, January 25, 2023最新文献

{"title":"Integrated History Matching Method for Horizontal Wells Using Advanced Pressure Transient Analysis","authors":"Ruicheng Ma, Shu Wang, Yixuan Zhao, Yong Li, D. Hu, Zeqi Zhao, Siying Hao, Yi-hang Chen","doi":"10.2118/212599-ms","DOIUrl":"https://doi.org/10.2118/212599-ms","url":null,"abstract":"\u0000 Horizontal wells have been applied in Middle East universally. However, with complex geological conditions including thief zone, aquifer and heavy oil, there are diverse production/injection performances for horizontal wells. Therefore, history matching is a tough job for reservoirs with horizontal wells. Pressure transient analysis (PTA) data is abundant and relatively economically obtained. With PTA technique, reservoir properties, streamline distribution and effective horizontal interval can be obtained easily. Therefore, history matching results could be identical with actual reservoir performance.\u0000 This paper proposes an optimized history matching method for horizontal wells assisted by advanced pressure transient analysis. Considering heterogeneity of layer-cake reservoir, a newly corrected method of log-log plot of PTA analysis is built to make a better interpretation under the effect of high permeability zone (HPZ). Then pressure transient analysis results will be validated with production/injection performance and other surveillance data such as resistivity logging. Finally, based on interpreted results, history matching is conducted. The advanced PTA model yields favorable interpreted results in accordance with production/injection performance and other surveillance data. Integrated history matching yields better results compared with typical workflow and modification of dynamic model. For several tough problems such as layer-cake reservoir with bottom aquifer, profile tuning is better than modification of grid property around wellbore.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"32 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":"127319361","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":"Advanced Porosity and Permeability Analyses Based on BHI Approach","authors":"Omar Mohammed Al Isaee, Dmitrii Smirnov, A. Al Hadhrami, Hilal AL Shabibi, F. Khayrutdinov, Fatma Khamis Al Jahwari, M. A. AL Raisi, Ibrahim Saleh Al-Maawali","doi":"10.2118/212665-ms","DOIUrl":"https://doi.org/10.2118/212665-ms","url":null,"abstract":"\u0000 Carbonate intrasalt stringers formation evaluation proved to be complex due to the nature of the rock lithology through syndolomitization and postdolomitization process. The need for the radioactive data is highly recommended, however different degrees of depletion along the reservoir units are posing clear threat to data acquisition. This study aims to establish an advanced model of calculating the porosity and permeability using non-radioactive BHI approach without compromising with the quality of the formation evaluation.\u0000 This study was conducted while facing the challenge of limited data acquisition with the pressure behavior across the carbonates stringers and the need to understand the nature of the permeability disturbance. The pilot covers two wells, Well-A was most useful regarding the source of the data for the analyses. Missing information was obtained from Well-B, which consist of the same dataset. The resistivity image data quality throughout the interpreted BHI section was good. Several analyses were carried out to characterise BHI data including fractures interpretation, porosity prediction (microfractures, intragranular pores and fluid inclusions) and permeability distribution (fracture aperture analysis).\u0000 Based on this study, the following observations are obtained, the predicted porosity and permeability are well correlated with the core and density – neutron data. The net pay identification and porosity calculation is consistent with those derived from density-neutron logs. Highly fracture zones were detected across the reservoir, which explain the permeability disturbance. Natural fracture tends to be found in clusters throughout the borehole. Conductive fracture, which has direct influence to the permeability were interpreted using the electrical borehole image to estimate the electrical apertures of open fractures around the wells. Pressure behavior across the reservoir might be linked to the natural fracture networks (conductive and non-conductive fractures). In the development side, this study helps to have better understanding of the rock typing and Lithotypes associated with different permeability clusters and reservoir quality integrated with production behavior.\u0000 The developed methodology of BHI evaluation provides reliable results in Porosity and Permeability evaluation. The model integrates relevant disciplines to evaluate intrasalt stringers dolomite and limestone mixed environment through independent lithology approach to eliminate the effect of the matrix heterogeneity. In addition, BHI approach provides safer logging acquisition and better option for advanced natural fracture analysis.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"51 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":"128257225","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":"Use of Deconvolution for Pressure Transient Analysis in Layered Reservoirs – A New Method","authors":"Mina S. Khalaf, Ahmed H. El-Banbi, M. Sayyouh","doi":"10.2118/212652-ms","DOIUrl":"https://doi.org/10.2118/212652-ms","url":null,"abstract":"\u0000 Many reservoirs exhibit multilayer behavior. Multilayer oil/gas reservoirs are usually classified as (1) systems with formation crossflow and (2) systems without formation crossflow (commingled systems). The focus in this work is the analysis of pressure transient data of commingled layers.\u0000 Pressure transient analysis for multilayer reservoirs to estimate individual layer properties is usually difficult and suffers from many limiting assumptions. The available interpretation methods are usually based on a subjectively presumed model (usually homogenous and isotropic layers, and radial infinite reservoirs) that has many unknown parameters (e.g., permeabilities and skin factors) to be estimated through a history matching process. The individual layer properties obtained from such analysis methods may not be reliable. The reliable way to evaluate individual layers’ characteristics is to isolate and test each layer separately, which is challenging due to high costs and occasional operational constraints.\u0000 In this work, we suggest a testing procedure and an analysis approach to analyze well test data of commingled reservoirs that allows reliable characterization of individual layers. The approach benefits from modern deconvolution techniques to eliminate the rate variation (rate transients) effects from the bottom-hole pressure signal acquired during the test. The methodology presented does not make assumptions about the individual layer reservoir models and recovers distinct pressure signals of the individual layers. The recovered pressure signals of each layer are also free of wellbore storage (WBS) effects. In addition, the individual layers’ pressure signals are stretched over the whole test duration (both drawdown and buildup periods).\u0000 Successful application of deconvolution requires complete sandface rate data of the individual layers in the commingled system. However, the continuous measurement of individual layers sandface rates is usually not available. A simple model is introduced in this work to make good estimations of the layer rate profile using few measurements of the production logging tool (PLT). The developed rate profiles are then used in deconvolution and individual layer's pressure signal can be recovered for further analysis.\u0000 The approach was verified against simulated cases with variety of layer models. The results obtained from the developed approach are in good agreement with the true solution. The findings of this study can be used to characterize commingled reservoir systems and determine the individual layers properties. It has applications in optimizing injection/production well performance of commingled systems.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"29 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":"117014772","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":"Deep-Learning-Based Surrogate Model to Predict CO2 Saturation Front in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach","authors":"Zeeshan Tariq, Zhen Xu, Manojkumar Gudala, B. Yan, Shuyu Sun","doi":"10.2118/212658-ms","DOIUrl":"https://doi.org/10.2118/212658-ms","url":null,"abstract":"\u0000 Naturally fractured reservoirs (NFRs), such as fractured carbonate reservoirs, are ubiquitous across the worldwide and are potentially very good source to store carbondioxide (CO2) for a longer period of time. The simulation models are great tool to assess the potential and understanding the physics behind CO2-brine interaction in subsurface reservoirs. Simulating the behavior of fluid flow in NFR reservoirs during CO2 are computationally expensive because of the multiple reasons such as highly-fractured and heterogeneous nature of the rock, fast propagation of CO2 plume in the fracture network, and high capillary contrast between matrix and fractures. This paper presents a data-driven deep learning surrogate modeling approach that can accurately and efficiently capture the temporal-spatial dynamics of CO2 saturation plumes during injection and post-injection monitoring periods of Geological Carbon Sequestration (GCS) operations in NFRs. We have built a physics-based numerical simulation model to simulate the process of CO2 injection in a naturally fractured deep saline aquifers. A standalone package was developed to couple the discrete fracture network in a fully compositional numerical simulation model. Then reservoir model was sampled using the Latin-Hypercube approach to account for a wide range of petrophysical, geological, reservoir, and operational parameters. The simulation model parameters were obtained from extensive geological surveys published in literature. These samples generated a massive physics-informed database (about 900 simulations) that provides sufficient training dataset for the Deep Learning surrogate models. Average Absolute Percentage Error (AAPE) and coefficient of determination (R2) were used as error metrics to evaluate the performance of the surrogate models. The developed workflow showed superior performance by giving AAPE less than 5% and R2 more than 0.95 between ground truth and predictions of the state variables. The proposed Deep Learning framework provides an innovative approach to track CO2 plume in a fractured carbonate reservoir and can be used as a quick assessment tool to evaluate the long term feasibility of CO2 movement in fractured carbonate medium.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"7 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":"130899691","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":"Fluid Monitoring to Optimize GOGD Recovery in Highly Fractured Reservoir Field in North of Sultanate of Oman","authors":"Azza Al Hussaini, Kholood Al Nofli, K. Agarwal, M. Abri","doi":"10.2118/212687-ms","DOIUrl":"https://doi.org/10.2118/212687-ms","url":null,"abstract":"\u0000 Gas oil Gravity Drainage (GOGD) process is one of the highly efficient recovery mechanism in heavily fractured carbonate reservoirs. The driving force is the gravity, the oil is moving down from the matrix block through fractures until it reaches the producers. To ensure optimum offtake from the reservoir through the horizontal wells the oil rim need to be stabilized and very well managed through the gas injection, offtake/intake balance, aquifer pump off.\u0000 A key challenge of optimizing the gas injection as well as the offtake from the horizontal wells to achieve effective GOGD recovery is to ensure that a minimum oil rim thickness is maintained, and that oil rim is kept at the same depth as the oil production well. If not;\u0000 When the oil rim moves down, the well will produce gas instead of oil, therefore resulting in deferment and inefficient GOGD recovery. When the oil rim moves up, the well will produce water from the fracture system, therefore resulting in deferment and significant time to recover the oil rim to the correct depth.\u0000 A typical monitoring method for the fracture fluid fill is to run \"gradio\" surveys in dedicated observation wells to measure the fGOC and fOWC (where \"f\" represent the fracture system contacts i.e. fractured gas oil contact and fractured oil water contact rather than the matrix contacts). Also the fluid movement in matrix can be monitored by Pulsed-Neutron logging, in combination with Open-hole logs that have been acquired at different times through the development.\u0000 In addition to the logging methods, GOGD Flow Unit characterization was introduced to depict the effect of the intake/offtake changes and oil rim movement within the GOGD system along with a surveillance strategy focusing on reservoir optimization. Fluid contact visualization plots were generated for each flow unit which give a clearer picture in how effective is the current GOGD system and the future reservoir development and optimization.\u0000 More than 5 flow units with almost 150 active wells,3 gradio wells and 5 pulsed neutron log data were reviewed, to generate fluid contact visualization plots and justify flow unit production behavior. This analysis initiative helped to depict the effect of the intake/offtake changes and oil rim movement within the GOGD system. This work also led to adding additional development opportunities like placement of future new wells or adding perfs /carrying out zone change in existing closed in wells either to produce oil or to pump off water. This eventually fed into the reservoir optimization and surveillance strategy.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"239 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":"132735006","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":"Physics Informed Surrogate Model Development in Predicting Dynamic Temporal and Spatial Variations During CO2 Injection into Deep Saline Aquifers","authors":"Zeeshan Tariq, B. Yan, Shuyu Sun","doi":"10.2118/212693-ms","DOIUrl":"https://doi.org/10.2118/212693-ms","url":null,"abstract":"\u0000 Geological Carbon Sequestration (GCS) in deep geological formations, like saline aquifers and depleted oil and gas reservoirs, brings enormous potential for large-scale storage of carbon dioxide (CO2). The successful implementation of GCS requires a comprehensive risk assessment of the confinement of plumes at each potential storage site. The accurate prediction of the flow, geochemical, and geomechanical responses of the formation is essential for the management of GCS in long-term operations because excessive pressure buildup due to injection can potentially induce fracturing of the cap-rock, or activate pre-existing faults, through which fluid can leak. In this study, we build a Deep Learning (DL) workflow to effectively infer the storage potential of CO2 in deep saline aquifers. Specifically, a reservoir model is built to simulate the process of CO2 injection into deep saline aquifers, which considers the coupled phenomenon of flow and hydromechanics. Further, the reservoir model was sampled to account for a wide range of petro-physical, geological, and operational parameters. These samples generated a massive physics-informed simulation database (about 1500 simulated data points) that provides training data for the DL workflow. The ranges of varied parameters were obtained from an extensive literature survey. The DL workflow consists of Fourier Neural Operator (FNO) to take the input of the parameterized variables used in the simulation database and jointly predict the temporal-spatial responses of pressure and CO2 saturation plumes at different periods. Average Absolute Percentage Error (AAPE) and coefficient of determination (R2), Structural similarity index (SSIM), and Peak Signal to Noise Ratio (PSNR) are used as error metrics to evaluate the performance of the DL workflow. Through our blind testing experiments, the DL workflow offers predictions as accurate as our physics-based reservoir simulations, yet 300 times more efficient than the latter. The developed workflow shows superior performance with an AAPE of less than 5% and R2 score of more than 0.99 between actual and predicted values. The workflow can predict other required outputs that numerical simulators can typically calculate, such as solubility trapping, mineral trapping, and injected fluid densities in supercritical and aqueous phases. The proposed DL workflow is not only physics informed but also driven by inputs and outputs (data-driven) and thus offers a robust prediction of the carbon storage potential in deep saline aquifers with considering the coupled physics and potential fluid leakage risk.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"31 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":"133935922","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":"Numerical Simulation Modelling of Well Tests for a Frac-Pack Completion Well in a Shallow Sand Reservoir","authors":"Seyed Mousa Mousavi Mirkalaei, E. Motaei, Anwar Husen Akbar Ali","doi":"10.2118/212649-ms","DOIUrl":"https://doi.org/10.2118/212649-ms","url":null,"abstract":"\u0000 Understanding the flow behaviour of fractured wells is crucial to operators and service companies in evaluating the effectiveness of stimulation work performed on the well. New insights in modelling of well transient pressure tests in hydraulic fractured unconsolidated sand is presented in this paper by utilizing 3-D numerical black oil simulation in single and two layered sand reservoirs with a thin shale layer in between. The upper layer perforated and fractured to treat the sand production as frack-pack technique and the well test has been conducted only on the upper layer. Porosity and permeability heterogeneities are classically evaluated from petrophysic well log measurements and through geological description of the reservoir, then possibly refined by simulation and history matching. The pressure measured in the well test in four cycles of drawdown and build up. The well bottom hole pressure (BHP) behaviour cannot be adequately described with conventional well tests analysis for the upper sand without including the flow from the lower sand.\u0000 Different scenario of production from upper with adding hydraulic fractured examined to match the oil/gas production and bottom hole pressure. A range of factors are examined that may impact the introduced fracture flow behaviour based on actual fractured well flow. The main fracture and reservoir parameters investigated include absolute permeability of upper layer, gas oil contact (GOC), relative permeability endpoints to oil and gas, hydraulic fracture properties (permeability, width) and extension and finally the skin factor.\u0000 The results of dynamic simulation model show that the model is very sensitive to the amount of gas production and hydraulic fracture vertical extension. We highlight through this example and sensitivity simulations that the GOC should be very close to the well preformation or else the pressure could not be matched. Hydraulic fracture vertical extension is required for matching of BHP and gas rate, without it, the gas rate will be very high in all of the simulation cases. The fracture connecting the upper layer to lower layer with only upper layer perforated. Absolute permeability from log cannot represent to the real permeably measured from well test. To match all historical data absolute permeability, need to be reduce by one order of magnitude. Finally, the model is sensitive to the skin factor for matching of pressure build up.\u0000 The main business questions were answered through integrated analysis of the analytical well model and dynamic simulation of single model to identify the source of excess gas and understand the well performance to reduce the uncertainty in production forecast. Fast approach in the single well modeling and efficient approach in the integration in the workflow is described in detail in the paper.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"1 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":"114137584","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":"Assessment of the Influence of Fault-Associated Fracture Corridors Through Integrated Geological-Engineering Sector Screening: A Game Changer for Optimizing Reservoir Management Practices in a Giant Carbonate Onshore, Abu Dhabi U.A.E.","authors":"R. Farnetano, R. Gutiérrez, A. Freites, K. Torres, Eiman Alnuaimi","doi":"10.2118/212675-ms","DOIUrl":"https://doi.org/10.2118/212675-ms","url":null,"abstract":"\u0000 The sector screening review is a surveillance tool used to assess and find opportunities to increase the oil production and improve the performance of the reservoir. We developed a novel interdisciplinary workflow (geology-engineering) integrating dynamic and static data in order to generate opportunities at well and field level; this methodology was used to analyze the impact of fractures in the reservoir performance and management.\u0000 The complexity of the geology on areas near a graben system (structure at center of the field with biggest vertical displacement) was suspected to cause flow anomalies that ultimately affected the well productivity indexes. After an exhaustive evaluation, it was noticed that a well showed lower productivity index (PI), 2-3 times less than nearby producers in the area, same reservoir Unit Z2 (similar lengths, conditions). To understand the root cause of such performance, a geoengineering workflow was implemented, integrating pressure transient analyses (PTA), production logging (PLT), bottom hole image (BHI), seismic (exceptionally complete dataset) and extrapolated to other wells with similar behavior.\u0000 The PLT showed that 70% of the well contribution was concentrated in only a small interval of the horizontal section, this interval was correlated to a conductive fault through BHI, which was also detected by seismic (correlates with low velocity anomaly). The PTA showed unexpected pressure transient behavior suspected to be related to the dynamic effect of the fault and associated fractures.\u0000 Learnings from above analyses triggered actions in different scales/stages: at Well scale, 1st Stage: the well was selected to be completed using selective stimulation with abrasive jet, to remove damage of the first 400 ft. of the well (skin factor masked by fracture contribution) and unlock the potential of non-contributing zone (after fault, to toe); allowing the well to produce 25% additional oil and doubling the PI. 2nd Stage (planned): workover proposal to install lower completion (LC), to ensure even depletion, avoid by-passed oil and prevent early water/gas breakthrough. Field scale: new wells to be drilled in reservoir zones potentially affected by the graben will be equipped with LC. Finally, a geological well testing framework matching the PBU and PLT was implemented based on a high resolution geological model designed to capture the properties of the matrix and fractures. The results from this study were used as diagnostic tool for additional wells with similar conditions which lack PLT data.\u0000 Noticeably, the presence of flow controlling fractures was usually suspected but not properly assessed/quantified in this reservoir, mainly due to the fact that the dynamic impact of these fractures was masked by the overlapping of different geological phenomena. The implementation of our geological-engineering workflow allowed immediately triggering actions that could lead to major performance enhancements at field- and wel","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"265 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":"114194077","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":"Advanced Thermo-Fluid Dynamic Well Model for RTVFM Flow Rates Estimation","authors":"Erica Grelli, F. Ursini, Emanuele Vignati, A. Piccolo","doi":"10.2118/212685-ms","DOIUrl":"https://doi.org/10.2118/212685-ms","url":null,"abstract":"\u0000 The availability of a simple and robust flow allocation system is of primary importance for reservoir management since it provides oil, water, and gas production for each well.\u0000 The low frequency of well separator tests and the difficulties in performing regular maintenance of multiphase flow meters have led to the development of Real Time Virtual Flow Meter (RTVFM) in Eni, a numerical solution to obtain real time flow rate estimation from pressure/temperature gauges measurements. This paper discusses the implementation and application of a novel RTVFM algorithm that increases the accuracy, stability, and robustness of the existing numerical tools even in case of extreme oil field environment with significant uncertainties.\u0000 Current Virtual Meter algorithms are based on fluid dynamic simulators which calculate the pressure drops through wellbore, choke, and flowlines; the algorithm can be run in real time to find the optimal production rates that minimize the error between physical pressure readings and the calculated ones. In this work, a constraint is added to the system by including the temperature matching in the objective function, further improving the tool reliability. An accurate heat transfer characterization of the well has been implemented to predict the temperature changes along the wellbore during time, as well as the thermal effect due to pressure variations (Joule-Thompson effect).\u0000 The effectiveness of the implemented algorithm has been proven by its application on a few offshore oil producers. In the chosen wells, equipped with dedicated MPFMs, the production measurements are not always reliable and RTVFM can be a valid support tool for back allocation. However, the flow rate estimation can be affected by significant uncertainties like production parameters variability (water cut and gas oil ratio) and fluid properties variation due to gas re-injection or artificial gas lift. In this scenario, the proposed enthalpy balance model allows to find a unique solution for the flow rate estimation, while the algorithm based only on pressure readings can converge to multiple solution rates.\u0000 Increasing the accuracy of RTVFM tool is imperative to allow a reliable back allocation process, even in case of MPFM unavailability, poor sensors data quality and highly variable fluid properties. This paper investigated how an advanced thermo-fluid dynamic model can improve Virtual Meter algorithms, thus reducing the uncertainties in the numerical flow rate estimation.","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"85 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":"127009218","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":"Integration of Production Data Analysis in Ensemble History Matching","authors":"Mohamed Amr Aly, P. Anastasi, E. D. Rossa, Angelo Ortega, S. Renna","doi":"10.2118/212679-ms","DOIUrl":"https://doi.org/10.2118/212679-ms","url":null,"abstract":"\u0000 The reservoir model-based forecast uncertainty reduction requires the integration of multiple sources of information. Among them, production data are of great value. For this reason, a methodology able to manage them within the history matching process to improve the model calibration process is highly recommended. The scope of the activity is then to set up a new workflow able to fully integrate Production Data Analysis (PDA) with an Ensemble History Matching (ENHM) workflow.\u0000 PDA outcomes represent evidence highlighted by the whole production history based on the collection, analysis, and integration of all available geological and dynamic data, such as injector-producer connections. A set of alternative realizations (\"ensemble\") needs to be created representing all the relevant uncertainties. Ensemble Screening is necessary to eliminate the non-PDA compliant realizations; comparing streamlines generated on the ensemble with the PDA outcomes and eliminating the non-representative realizations. Ensemble diagnostic tools can help to discriminate the ensemble consistency with the basic reservoir facts coming from PDA and which parameters or assumptions in the ensemble creation need to be revised because of the non-compatibility from a statistical point of view (like conflicting or insufficient parameterizations). The ensemble will be matched through the ENHM iterative process. The proposed workflow uses then the Fluid Path Conceptual Model (FPCM) derived from PDA, as a key driver to localize the model updates performed by the iterative ensemble process.\u0000 The proposed workflow allows obtaining a set of realizations representative of both the main geological and dynamical features of the field. This in turn will result in a higher predictive quality of the model-based forecasts. The performed tests allow us to conclude that PDA outcomes provide significant information regarding the fluid communications that can improve the ensemble reservoir parameterization reducing the reservoir uncertainties. Ensemble distance computation based on streamline attributes, like Time of Flight and streamline normalized fraction, can find similarities among realizations reflecting the connectivity patterns relevant to the PDA perspective. The evidence highlighted from PDA can be used as firm input in the ensemble realizations generation also impacting fundamental steps, such as the geological setup. Moreover, PDA can help to identify the main uncertainty parameters characterizing the field and suggests a reasonable range of variability to be considered within the ensemble approach.\u0000 Multiple ensemble diagnostic tools were developed to check the ensemble quality against PDA outcomes using different streamline attributes as a distance. Diagnostic tools, moreover, allow to identify a reduced number of model realizations representative of the ensemble variability on which run the forecast. The advantages of the proposed workflow can balance the unavoidable additional ti","PeriodicalId":215106,"journal":{"name":"Day 2 Wed, January 25, 2023","volume":"99 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":"114851991","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}