bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models
Authors: Yang Changdong , He Jincong , Onishi Tsubasa , Du Song , Wang Zhenzhen , Guan Xiaoyue , Chen Jianping , Wen Xian-huan 
Published: March 2022

Summary
Full-physics subsurface simulation models coupled with the surface network can be computationally expensive. In this paper, we propose a physics-based subsurface model proxy that significantly reduces the run time of the coupled model to enable rapid decision-making for reservoir management.
In the coupled model, the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves that are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the computationally intensive reservoir simulation is replaced with an IPR database constructed from a data pool of one or multiple simulation runs. The IPR database captures well performance that represents subsurface reservoir dynamics. The proxy model can then be used to predict the production performance of new scenarios—for example, new drilling sequence—by intelligently looking up the appropriate IPR curves for oil, gas, and water phases for each well and solving it with the surface network. All necessary operational events in the surface network and field management (FM) logic (such as facility constraints, well conditional shut-in, and group guide rate balancing) for the fully coupled model can be implemented and honored.
In the proposed proxy model, the reservoir simulation component is eliminated for efficiency. The entirety of the surface network model is retained, which offers certain advantages. It is particularly suitable for investigating the impact of different surface operations, such as maintenance schedule and production routing changes, with the aim of minimizing production capacity offline because of maintenance. Replacing the computationally intensive subsurface simulation with the appropriate IPR significantly reduces the run time of the coupled model while preserving the essential physics of the reservoir. The accuracy depends on the difference between the scenarios that the proxy is trained on and the scenarios being evaluated. Initial testing with a complex reservoir with more than 300 wells showed the accuracy of the proxy model to be more than 95%. The computation speedup could be an order of magnitude, depending largely on the complexity of the surface network model.
Prior work exists in the literature that uses decline curves to replicate the subsurface model performance. The use of the multiphase IPR database and the intelligent lookup mechanism in the proposed method allows it to be more accurate and flexible in handling complexities such as multiphase flow and interference in the surface network.
Fault Rock Property Prediction on Jurassic Clastics of the Barents Sea, Norway
Authors: Schuller Volker , Zamolyi Andras , Stueland Eirik , Dunkl István , Kettermann Michael , Schleder Zsolt 
Published: March 2022

Summary
We analyzed the fault rocks of a compartmentalized field in the Barents Sea, in an area with several tectonic elements, which formed at different tectonic events. Standard fault seal analysis (FSA) was conducted to predict the shale content of the fault rock (shale gouge ratio, SGR). A static cellular model based on well data, seismic data, and geological concepts served as input. The fault rock calibration workflow required various data acquired by different methods. We analyzed the Middle Triassic to Upper Jurassic clastic deposits to reconstruct the tectonic history. Apatite fission track (AFT) and (U-Th)/He thermochronology were used to determine the maximum burial depths and exhumation history. The results of high-resolution shale ductility analysis, a compaction trend study, kinematic analysis, and structural modeling (section balancing) served as additional input constraints for fault rock calibration.
The interpretation of the results helped to reconstruct the following tectonic evolution. The orthogonal faults developed shortly after deposition, during Late Triassic to Early Jurassic times at relatively shallow depth, below 1000 m. Ongoing subsidence created accommodation space for Upper Jurassic to Cenozoic deposits with a maximum burial depth of 2000 m for the Middle Jurassic rocks. Exhumation of the area started around 10 Ma and continued through to Quaternary times.
The predicted across-fault-flow values for fault rock permeability show a wide range when using poorly constrained input for fault rock calibration: 9.9E−15 to 9.9E−13 m² for SGR values around 0.08 at reservoir/reservoir juxtaposition. Fault rock calibration using elaborated results reduced the uncertainty of fault rock permeability estimates, and ultimately, for transmissibility multipliers (TMs). The reason for the sensitivity of the fault rock calibration is a combination of following factors: highly permeable reservoir sandstone, shallow depth of initial faulting, maximum burial depth and low shale content at the upper, main reservoir level.
The study shows that an accurate reconstruction of the geohistory provides essential parameters for fault rock calibration and fault rock permeability prediction. The range of values can widely scatter if boundary conditions are not acknowledged. Well-constrained fault rock calibration reduces the uncertainty on possible flow scenarios, increases the reliability on production forecasts and helps determine the most efficient drainage strategy.
What is Next for SAGD?: Evaluation of Low GHG and High-Efficiency Tertiary Recovery Options
Authors: Pratama Randy Agra , Babadagli Tayfun 
Published: March 2022

Abstract
Steam injection has been widely applied in different forms to recover heavy-oil and bitumen for decades. Even though this method is a proven and effective technology, the steam generation process itself may lead to environmental issues and low economic viability. Also, many worldwide steam projects, including SAGD projects in Canada, have already reached their maturity with a severe decline in production despite continuous steam injection. Escalating greenhouse gas (GHG) emissions is another crucial downside of steam injection application, contributing to an emission growth rate of about 1.1% worldwide and 0.8% annually in Canada. This requires us to search for different techniques to deplete the remaining (conditioned) oil efficiently and in an eco-friendly manner. This paper focuses on the testing of a new technique to minimize GHG emissions resulting from steam generation while enhancing the ultimate recovery post-SAGD.
~50,000 cP heavy crude and processed oil (for visual models) samples were used as an oleic phase in this experimental research. Condensable gases as single and multiple (mixed with methane) components were included as potential solvents to be applied to the already steamed models. Visual Hele-Shaw and glass-bead-pack models were employed to investigate the displacement mechanism, displacement efficiency, and phase distribution in porous media. All experiments were performed at currently existing temperatures in matured SAGD reservoirs to further evaluate the sensitivity of phase behavior of condensable solvents in a heavy-oil/steam system, as well as existing condensed water of which is not compatible with hydrocarbon solvents.
We observed that condensable solvents could improve the displacement efficiency/incremental heavy-oil recovery over 30% by mobilizing residual oil and providing favorable conformance to the steam chamber. More importantly, the steam usage was able to be entirely cut off, and the energy efficiency could be ramped up to almost 100%. Additionally, the type (and composition) for applying condensable solvents were determined at a given post-SAGD temperature. Also, the retrieval potential of the condensable solvent with oil was investigated for an efficient process.
Condensable gases with different compositions were introduced as potential solvents to recuperate heavy-oil and bitumen recovery and reduce or even completely cut off the steam injection at late-stage SAGD, diminishing its GHG emission and improving energy efficiency. Valuable findings present beneficial recommendations for low-emission and high-efficiency late-stage heavy-oil recovery as post-SAGD applications, as well as other types of steam injection processes.
Refracturing Candidate Selection in Tight Oil Reservoirs Using Hybrid Analysis of Data and Physics Based Models
Authors: Hu Die , Lei Zhengdong , Cartwright Stephen , Samoil Steven , Xie Siqi , Chen Zhangxin 
Published: March 2022

Abstract
Refracturing candidate selection problems can be solved via production statistics, virtual intelligence and type-curve matching, and these methods are mostly developed using data-based models. They unleash great power of data but have not considered the influence of geological distributions in physics-based models. This paper combines the strengths of data and physics based models and proposes a hybrid analysis method to improve and strengthen the current methods.
Three criteria, production performance, a completion index and a geological distribution around an offset well, and their sub-criteria are selected to build an evaluation system for refracturing candidate wells. Field data is collected and processed to calculate a completion index and production performance. To quantify a geological distribution around a well, a history-matched reservoir simulation model is required. Besides, a graph theory algorithm, Dijkstra’s shortest path, is used to quantify the influence of geological distributions in 3D reservoir models on wells. An analytic hierarchy process and grey correlation analysis are then used to establish a multi-level evaluation system and determine and rank each individual strategic factor. Finally, datapoints are shown in a 3D coordinate system, and custom defined weights are used to calculate the final ranking of potential refracturing wells. In addition, the hybrid analysis is presented on our self-developed visualization platform.
A history-matched reservoir simulation model from the Y284 tight oil reservoir is used as a study case. Eight refractured wells’ data is collected and analyzed. As a grey correlation analysis result, a sub-criteron of productivity performance, relative productivity, ranks the first, followed by cumulative liquid production. Completion and resistance rank third and fourth with a small gap. Based on the analysis results, an evaluation system is built up. 14 refracturing candidate wells are analyzed and ranked using the evaluation system. These wells are displayed in a 3D coordinate system, where x, y and z directions represent three criteria separately. Wells distributed in the first quadrant are regarded as optimum candidates to apply refracturing treatments. Correlations of evaluation factors and increased oil production after refracturing treatment are plotted to validate the method.
This study explores how to conduct hybrid analysis in a selection workflow of refracturing candidate wells. Combing visualization, interpretability, robust foundation and understanding of reservoir models with accuracy and efficiency, data-driven artificial intelligence algorithms, the experiences distilled, and insights gained from this project show great potential to apply hybrid analysis as well as modelling in oil and gas industry.
Advanced Reservoir Control Systems Paving the Way for Digital Offshore Operations and Analysis
Authors: Garcia Elias , Robertson Kevin 
Published: March 2022

Abstract
Digital offshore operations and analysis rely on the deployment of downhole completion technologies that can produce significant quantities of data. Historically, downhole monitoring technologies, such as fiber optics and permanent downhole gauges, have been a good source of wellbore data for modeling and analysis. Permanent downhole monitoring technologies have benefitted from the advancement of high temperature electronics, reducing overall power consumption, and directly affecting sensor and electronics reliability and longevity. Through the utilization of telemetry schemes for addressability, permanent downhole monitoring technologies have also helped to develop electro-hydraulic and all-electric downhole flow control technologies, by enabling increased wellbore compartmentalization and fast control of multiple wellbore intervals.
Advanced reservoir control systems have the ability to integrate to smart and data driven systems. They can be subdivided into extrinsic and intrinsic systems. Intrinsic systems benefit from having integrated monitoring technologies that can be addressed through telemetry schemes, which are also used to control multiple wellbore intervals. Examples of intrinsic systems include intrinsic electro-hydraulic systems and all-electric systems. To date, plenty of testing has been done with these types of intrinsic systems, but this paper highlights the evaluation of an intrinsic electro-hydraulic system.
Ultimately, the authors believe that a stepwise approach through the implementation of hybrid-electric digital systems is key to the overall acceptance of all-electric systems. The success and reliability of electro-hydraulic systems will play a significant role in mass acceptance of all-electric systems in the oilfield. Electro-hydraulic systems are a good segway into all electric systems and give operators the chance to utilize some of the existing infrastructure while benefiting from some of the optimizations brought on by the Digital Oilfield.
Electromagnetic Induction Heating Technology for Enhanced Heavy Oil and Bitumen Recovery
Authors: Sherwali Ahmed , Noroozi Mehdi , Dunford William G. 
Published: March 2022

AbstractThis paper demonstrates how a novel electromagnetic induction heating technology can be used to recover oil from the Athabasca oil sands of Alberta with minimal environmental impact. The paper compares the new technology to other electromagmetic heating technologies for oil sands, exhibits how electromagnetic induction heating is coupled to the reservoir, and addresses requirements of the new technology for economic production.The patent pending inductor design generates thermal energy in a reservoir model representing a 33 meter pay zone with properties for the lower McMurray formation in an area north of Fort McMurray within the Athabasca oil sands deposit. Electromagnetic energy is coupled to the reservoir in an iterative process that enables operators to monitor and control reservoir temperature, pressure, fluid production, and energy to oil ratio, to enhance recovery of heavy oil and bitumen. This is performed by interfacing commercial electromagnetic and reservoir simulators using an in-house coupling script.The results demonstrate an ultimate oil recovery factor of +70% with an energy to oil ratio lower than 200 kilowatt hour per barrel. This is less energy per barrel than the average energy required by steam assisted gravity drainage. Though not compulsory for the process, it is observed that oil recovery is improved with water injection. This is mainly because the amount of electromagnetic energy coupled to the reservoir correlates with water saturation in the near wellbore region. Water injection helps maintain water saturation levels and improves heat convection further into the reservoir. Nonetheless, there is no need for external water supply, because the volume of injected water required to improve oil recovery is comparable to the overall volume of water produced from the reservoir.Unlike other recovery methods, this technology is expected to have low energy intensity, zero emissions, and minimized land footprint leading to responsible bitumen recovery. This paper sheds light on the capability of an innovative clean energy technology to enhance bitumen recovery from the Athabasca oil sands in Alberta. The novel technology takes advantage of clean energy to recover oil at a lower energy to oil ratio than the average ratio achieved with steam injection methods.
A Novel Procedure for Analyzing Production Decline in Unconventional Reservoirs Using Probability Density Functions
Authors: Alimohammadi Hamzeh , Sadeghi Mehdi , Chen Shengnan Nancy 
Published: March 2022

Abstract
In the past several decades, traditional decline curve analyses have been widely used as a quick and simple yet efficient method for reserve estimation and production forecasting. Several new models have been proposed since 2000s to address limitations of traditional decline models in shale and tight reservoirs especially multiple flow regimes and long-tail behavior of production profile which results in overestimating the reserve by the traditional models. Several of these newly proposed decline curve analysis (DCA) models are conservative and provide pessimistic reserve estimates.
The main purpose of this work is to evaluate the application of six heavy-tailed probability density functions (PDFs) to approximate production in shale and tight reservoirs. A new class of DCA model suitable to capture the production decline trend in shale and tight reservoirs is examined using real and simulated production data. The proposed class of DCA has been demonstrated to predict production more accurately in tight and shale reservoirs especially when only limited data are available from wells with less than a few months of production history.
A Step-Change Improvement in Fluid Diversion, Oil Sweep Efficiency, and CO2 Storage Using Novel Nanoparticle-Based Foam
Authors: Telmadarreie Ali , Johnsen Christopher , Bryant Steven 
Published: March 2022

Abstract
A significant amount of hydrocarbon in reservoirs is inaccessible even after deploying enhanced oil recovery methods such as gas, water, and chemical injections. Foams have been used for mobility control and fluid diversion for gas-based enhanced oil recovery, but they often lack stability in reservoir conditions. This study introduces the application of highly stable nanoparticle-based foam (nanofoam) for gas and water diversion and improving sweep efficiency and CO2 storage.
A series of flow experiments in uniquely designed dual porous media were performed to investigate the performance of nanofoam in fluid diversion, sweep improvement, and CO2 storage. A permeability contrast of 5 was created to mimic the heterogeneity and fluid diversion capability of different fluids including CO2 gas, water, surfactant-based CO2 foam, and nanofoam. High permeability and low permeability porous media were saturated with water and oil (viscosity of 20 cp) respectively, mimicking a swept thief zone and bypassed oil zone. Two different types of nanoparticles were used to stabilize the nanofoam (silica-based and cellulose-based nanoparticles). These nanofoams were compared with a conventional foam stabilized only by surfactant.
Due to high mobility contrast, injecting CO2 and water resulted only in displacement of water from the high permeability core, with negligible flow into the oil-saturated core. Foam was then injected with the intention of preferentially filling the high permeability core, so that subsequent CO2/water injection would be diverted into the oil-saturated core. Although surfactant foam generated relatively strong foam, it failed to divert subsequent water/CO2 into the oil-saturated core. The amount of oil recovery and additional CO2 storage was minimal. On the other hand, nanofoam (made with either type of nanoparticles) diverted both water and CO2 to the low permeability media improving oil recovery and increasing CO2 storage. Compared to pure CO2/water injection, nanofoam enhanced the incremental oil recovery by 40% of original oil in place with additional CO2 storage.
This study reveals that an engineered designed nanofoam could result in step-change improvement of conventional foams performance hence delivering the results desired in field applications. A highly stable foam can play an important role to access more pore space for CO2 storage and which is inaccessible otherwise without drilling new wells.
Flowback Pattern-Recognition to Distinguish Between Formation and Fracturing Water Recovery
Authors: Liu Zhanyuan , Moussa Tamer , Dehghanpour Hassan 
Published: March 2022

Abstract
We analyze flowback production data of 502 multi-fractured horizontal oil and gas wells completed in the Montney Formation and 83 oil wells completed in the Duvernay and Horn River Formations. The main goal of this paper is to evaluate the possibility of distinguishing between formation and fracturing water based on the water-flowback response. We hypothesize that: 1) the slope of water-flowback harmonic decline (HD) profile is reversely proportional to formation water mobility, 2) the deviations from the unit slope on rate-normalized pressure (RNP) plots is proportional to the slope of HD, and 3) the slope of water-flowback HD correlates with the initial water saturation (Swi). To verify our hypothesis, we 1) classify the observed HD trends of water-flowback rate based on slopes, 2) construct RNP diagnostic plots of the studied wells, 3) analyze log data and estimate average Swi by using Archie equation (1952) for the studied wells. 4) investigate the effects of Swi on the water-flowback pattern. The results show that there are two distinct flowback patterns. The first flowback pattern shows sharp slope (&gt;10-41/day) of water-flowback HD profile and relatively high slope values (0.64 to 0.984 kpa/m3) of the corresponding RNP plots. However, the second pattern shows very low slope of HD (&lt;5 × 10-5 1/day), with some wells showing no significant decline of water rate through the entire flowback process, also relatively low slope values (0 to 0.23) of the corresponding RNP plots. Analysis of the log data shows a positive correlation between Swi and slope of water-flowback HD profile. We also found that the slopes are proportional to the slope of RNP. These results indicate that as Swi increases, slope of HD decreases and there is more deviation from the unit-slope on the RNP plots.