bluuebunny/crossref_metadata_2025_split huggingface dataset:
Super-Resolution Reconstruction of Reservoir Saturation Map with Physical Constraints Using Generative Adversarial Network
Authors: Doloi Nandita , Ghosh Somnath , Phirani Jyoti 
Published: January 2023

Abstract
Complete physics-based numerical simulations currently provide the most accurate approach for predicting fluid flow behavior in geological reservoirs. However, the amount of computational resources required to perform these simulations increase exponentially with the increase in resolution to the point that they are infeasible. Therefore, a common practice is to upscale the reservoir model to reduce the resolution such that numerous simulations, as required, can be performed within a reasonable time. The problem we are trying to solve here is that the simulation results from these upscaled models, although they provide a zoomed-out and global view of the reservoir dynamics, however, they lack a detailed zoomed-in view of a local region in the reservoir, which is required to take actionable decisions. This work proposes using super-resolution techniques, recently developed using machine learning methods, to obtain fine-scale flow behavior given flow behavior from a low-resolution simulation of an upscaled-reservoir model. We demonstrate our model on a two-phase, deal-oil, and heterogenous oil reservoir, and we reconstruct the oil saturation map of the reservoir. We also demonstrate how the network can be trained using dynamic coarse geological properties at various resolutions. The findings imply that even when coarse geological features and with limited resolution, the super-resolution reconstructions are able to recreate missing information that is close to the ground facts.
Reservoir Modelling to Predict the Effect of Cold Water Injection in Geothermal Pressure Transient Analysis
Authors: Mitra Purnayan , Darraj Nihal Mounir 
Published: January 2023

Abstract
Energy is one of the major components for defining the overall development of a country. Mankind utilizes energy to meet the requirements of daily processes. This energy can be extracted from the renewable as well as the non-renewable sources of energy. With global rise in the usage of non-renewable energy sources, there is a much concern for the green house gas emissions and climate change. Renewable sources of energy are therefore being exploited to reduce the consumption of conventional fuels and overall reduce the environmental impacts. While solar, wind and tidal energy have been in scope of research, geothermal reservoirs are also proving their potential as a renewable source of energy. Geothermal reservoirs are one of the cleanest and renewable sources of energy which can meet the rising global energy crisis. Proper exploration and exploitation of geothermal energy is therefore one of the key objectives of reservoir engineers to adopt this energy source. The challenge which lies is to find best fit analytical methods for pressure transient analysis of geothermal reservoirs. This is because the assumptions made to predict the pressure transient analysis in hydrocarbon reservoirs are not satisfied by geothermal reservoirs. Based on extended studies it has been assumed to choose the properties of injected fluid in the reservoir conditions. But the gap between the reality and prediction couldn't be minimized as the properties of the hot and cold fluid in the reservoir conditions vary non-uniformly with respect to time. In this paper the impact of cold water injection on pressure transient analysis of geothermal reservoir is studied by varying the temperature of the injectate cold water from room temperature to reservoir temperature.
Maximizing Oil Recovery Using a Chemical Application in Offshore Environment-Case Study
Authors: Khanifar Ahmad , Abdul Manap Arif Azhan 
Published: January 2023

Abstract
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.
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.
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.
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.
Hybrid Algorithm Predicts Asphaltene Envelope for Entire ADNOC Fluid Portfolio
Authors: Mogensen Kristian , Grutters Mark , Merrill Robert 
Published: January 2023

Abstract
Asphaltene precipitation can sometimes pose operational problems in medium-light oils because of the low asphaltene solubility. The purpose of this work is to develop a methodology to predict the asphaltene envelope for all fluid systems in ADNOC’s reservoir portfolio based on existing laboratory experiments. Such a model would then be able to predict potential precipitation risks for current and future field development projects, especially the ones involving gas injection.
The starting point for development of the predictive model for asphaltene onset pressure (AOP) is the 100+ lab measurements carried out over several decades, of which 65% involve a number of injection gases such as CO2, lean and rich hydrocarbon gas, as well as sour gas. We then matched each data set with an equation of state (EOS) to generate the entire onset pressure envelope. Based on the envelope data points, we applied a data-driven method to reproduce the key trends, and used this trained model as a novel predictive tool for new production scenarios without experimental AOP data.
We first tested the PC-SAFT model for our phase behavior calculations but found that the method, as implemented in the software package, often experienced convergence problems. The PR-78 cubic EOS was found to be more reliable with the ability to match the experimental data despite limited predictive power. We find that availability of AOP data for reservoir fluids swollen with injection gas makes the thermodynamic model much more robust compared to tuning to a few AOP data on the original reservoir fluid alone. A single AOP point is generally not sufficient to fully constrain the EOS model unless model parameters from other studies are brought into use. SARA analysis is not mandatory for the EOS tuning itself and was found not to be required for training any of the data-driven methods. We limited the predicted data sets to temperatures below 350 °F, since all our reservoirs have temperatures below this threshold. From the calculated envelopes, we saw a clear impact of fluid composition on the shape of the AOP curve relative to the saturation pressure curve, as expected. We now have a tool, which can accurately predict the AOP curve for a combination of reservoir fluids and injection gases, as the long as the injection gas composition remains within the range tested experimentally.
Asphaltene Flow Assurance Pre-Risk Evaluation Case Study to Establish Guidelines for CCUS in Arabian Gulf Carbonate Oil Field
Authors: Tange Masaaki , Hiraiwa Takeshi , Khlaifi Khuloud Tareq , Sakurai Risa , Bahri Sami , Abed Abdalla Abdelfattah , Uematsu Hiroshi , Makishima Ken , Inokuma Yuto , Sawata Masaru , Alkaabi Sultan Hamdan , Yonebayashi Hideharu 
Published: January 2023

Abstract
Carbon dioxide capture, utilization and storage (CCUS) has been recognized as a key technology to reduce CO2 emission. Among various CCUS technologies, CO2 enhanced oil recovery (EOR) has been widely implemented at an industrial scale in the E&P sector. However, it is well-known that CO2-mixed oil would cause asphaltene precipitation resulting in flow assurance troubles. Therefore, more advanced asphaltene-risk-managing technology can be an enabler to improve robustness of CCUS projects.
This paper presents a case study for a comprehensive series of asphaltene flow assurance pre-risk evaluation in Arabian Gulf Carbonate Oil Field at where the CO2 EOR is recognized as one of the highest potential technologies for full-field implementation. At first, sampling location was carefully selected considering the target reservoir's feature because the reliability of asphaltene study highly depends on sample representativeness. After the QA/QC of collected sample, asphaltene onset pressures (AOP) were measured at multiple temperatures under the CO2 mixing conditions in a straightforward experimental-design optimizing manner so that not only the evaluation accuracy could be improved but also the experimental cost could be minimized. The AOP measurements showed clear potential risks associated with CO2 injection. Subsequently, the numerical model analysis was conducted with Cubic-Plus-Association (CPA) EoS model to identify the risk area during CO2 injection. The analysis suggested that a risk would be caused at not only near-wellbore region at the sampling location but also tubing section / surface facility, furthermore, more seriously at the deeper location of target reservoir. Finally, CO2-induced asphaltene formation damage risk was investigated from the viewpoints of precipitated asphaltene particle size and pore throat size in the porous media. As a result, the clogging risks by CO2-induced asphaltene were estimated high in the target reservoir.
By virtue of the above comprehensive series of pre-risk evaluation, the asphaltene flow assurance risk associated with CO2 injection was identified field-widely. The evaluation findings suggested moving on to future actions such as more detailed formation damage risk evaluation and mitigation plan development. The phased approach for evaluating asphaltene flow assurance risk and the reverse engineering of sampling operational design from the experimental design made a worthy demonstration to reduce unnecessary cost and time while obtaining the key information to drive the project. The procedure in this work can contribute to establish a subsurface part of guideline for CCUS from viewpoints of asphaltene flow assurance risk evaluation.
Integration of Seismic Poisson Impedance Data with Real-Time Geomechanics and Real-Time 3D Ultra-Deep Resistivity Inversion Enabled New Opportunities in Developed Field
Authors: Abdulkarim Anar , Kharitonov Alexander , El Gezeery Taher M. , Haddad Mohamed Al , Halawah Yousif Ahmad , Sabea Salem Al 
Published: January 2023

Abstract
The Wara sandstone reservoir in the Minagish field of Kuwait Oil Company is a complex deposition of a typical pro-deltaic environment consisting of shaly-silty sandstone sequences W7-W1. Three sequences (W6, W5, and W3) were expected in the case study well. The objective was to set 9⅝-in. casing at the top of W6 and then drill through the Wara sequences to connect all of them and land and drill the lateral section within W3.
The W6 sequence is typically the primary target in the Wara formation, being thick and consistent throughout the field. The next logical step in developing the Wara reservoir was to study and investigate the minor W5 and W3 members. Due to poor correlation of W5 and W3 channels in offset wells, the geological target was selected based on seismic Poisson impedance. Historically, targeting the Wara formation occasionally resulted in multiple sidetracks due to drilling challenges. A real-time geomechanics service was utilized to overcome drilling challenges and real-time 3D ultra-deep resistivity inversion was implemented to optimize well placement.
An extensive pre-drilling study for geomechanical and ultra-deep resistivity inversion modelling helped to develop road map for an optimal and safe well-construction process. The study showed that utilization of real-time 3D ultra-deep resistivity (UDR) inversion would help to optimize well placement and maximize sweet-zone exposure. The original well design, mud properties, and drilling parameters were modified based on the geomechanical study. Additionally, real-time geomechanics services were utilized to monitor and control the drilling process to follow the road map, which helped to avoid drilling issues, geostop at the W6 channel, and finally to run the casing smoothly. Real-time 3D ultra-deep resistivity mapping in the lateral section helped the operator to drill through W6 and W5, land precisely, and drill the lateral in the W3 channel, which was well developed, as expected from seismic Poisson impedance analysis. Formation evaluation of lateral section showed an average porosity of 24 p.u., water saturation 11% and up to 3 D/cp mobility.
The application of real-time 3D ultra-deep resistivity inversion helped to triple the planned formation exposure and to discover a geometric extension of the above deposited channels (W6 and W5), which will help for future field development. The flow test showed the highest production rates from W3 of the field. The integrated approach described above was recommended to be utilized for all future Wara wells.
Improved Reservoir Characterization of Tight Carbonate Rocks using Multiple High-Resolution Logging While Drilling Technologies for Completion and Stimulation Optimization with Fishbone Technologies; A Case Study from Offshore Abu Dhabi
Authors: Al Abed Sundos , Khemissa Hocine , Kurokawa Susumu , Aki Ahmet , Fares Wael , Mubeen Muhammed , Chehabi Wissam 
Published: January 2023

Abstract
Objective of this real case study was to test new technology of stimulation in tight rock along the horizontal drain. The reservoir architecture corresponds to stacked zones interbeded of porous and dense rocks. The dense ensure a vertical seal between the reservoir zones. The thickness of theses layers are varing from an area to other. Stylolite and feaw fractures were mapped and occurred maily in the dense zones. The study showed that the fractures are bded confined and very rarely they put incommunication two porous zones.
The targeted reservoir lithology is predominantly limestone with variable percentages of dolomite (20 to more than 50%), exhibiting laterally variable micro to miso pore texture. Saturation calculations using conventional open hole logs data shows high uncertainty associated to quantifying movable from bounded fluid and their type.
A new real-time petrophysical data acquisition program, using Logging While Drilling (LWD) technologies, is implemented in this case study to estimate the proportion of connate and free fluid distributions along a horizontal well section and to predict permeability, to help decide for depth of perforation for stimulation and optimize lower completion design.
Physics Informed Machine Learning for Production Forecast
Authors: Manasipov Roman , Nikolaev Denis , Didenko Dmitrii , Abdalla Ramez , Stundner Michael 
Published: January 2023

Abstract
Understanding the reservoir behavior is vital knowledge required for various aspects of the reservoir management cycle such as production optimization and establishment of the field development strategy. Reservoir simulation is the most accurate tool for production forecast, but often it is very expensive from aspects of computational time and investment in the model building process. In this work, the machine learning methods for accurate production forecast that honor the material balance constraints are presented.
The presented hybrid model approach consists of several main components. The material balance constraints are necessary during the training process to avoid unphysical solutions and to honor conservation laws. For this reason, the Capacitance Resistance Model (CRM) was chosen due to its intuitive form and flexibility in describing reservoirs of various complexities. Another part of the solution is represented by powerful machine learning methods such as Generalized Additive Models (GAM), Gradient Boosting, and Convolutional and Recurrent Neural Networks. Neural Networks and Gradient Boosting methods are very popular machine learning techniques. However, in this work, it is demonstrated that GAM can also produce results comparable to the former methods while holding additional attractive properties. The basis functions of GAM are the splines, which are smooth functions with continuous derivatives. Such properties are very useful for optimization tasks. GAM is an extension of standard Generalized Linear Models (GLM), which provides rich tools for model explainability. It is hence also advantageous for the understanding how the reservoir behaves through such models.
The implemented approach was applied to the publicly available data with an existing history matched reservoir model for the offshore field with several injectors and producers. This allowed us to compare results and build machine learning models that describe communication between wells and can be further analyzed though the simulation model.
Machine learning methods are constantly improving at solving difficult problems, while it often suffers from nonphysical solutions and unexplainable models. The presented method holds the properties of explainable regression models while providing powerful predictability capabilities within material balance constraints. By no means does it try to replace the reservoir simulation but offers a complementary solution, which is reliable and necessary in cases where there is no full reservoir model available.
Application of Simulation Opportunity Index and Assisted History Matching for Fishbone Completion Strategy in the Existing Single Horizontal Well in Tight Gas Carbonate Reservoir
Authors: Bernadi Bondan , Al Shehhi Hajar Ali Abdulla , Abdulla Al Ameri Sara Saleh Abdulla , Omar Alawadhi Fatima , Ahmed Al Hosani Mariam , Mohamed Al Bairaq Ahmed , Kuzevanov Maksim , Shelepov Konstantin 
Published: January 2023

Abstract
The trajectory placement of a horizontal well that crosses a heterogeneous tight gas carbonate reservoir is one of the important elements that contribute to the success of well productivity. Proper placement can yield good production and vice versa improper placement may give low well productivity. An effort was studied to improve the well productivity from an existing single horizontal well that was initially placed in sub optimal location by implementing the Fishbones completion technology (work-over).
In this paper, Simulation Opportunity Index (SOI) has been selected as a method to indicate the remaining gas sweet spot throughout the reservoir. SOI integrates 3 independent components extracted from static and dynamic parameters; reservoir permeability-thickness, movable gas, and reservoir pressure from a historically-matched dynamic model. By utilizing SOI, a map of the prospective gas sweet spots can be created; hence low performance existing wells are utilized to exploit the surrounding potential sweet spots using Fishbones completion, which consists of tiny short needles with a maximum effective length of 32 feet placed along the horizontal section.
The study reveals that the Fishbones completion application on existing low-productive horizontal well can multiply the well productivity in multi-layer reservoir environment in addition to the significant production gain. Assisted History Matching (AHM) is used to explore the best scenario of Fishbones features combination, such as the number of Subs required as the container room to hold the needles, the optimum needles length, and the optimum lateral drain section to place the Subs and needles. Many sensitivities with the abovementioned variables are run at once, and the analysis is conducted to identify the most impacting parameter to bring the highest well recovery. The use of SOI method to scrutinize the best location of well candidatures for Fishbone application and the required Subs and needles placement is not only able to rejuvenate the performance of the problematic well, but it can aid in generating CAPEX saving and efficient project schedule to manufacture Fishbones with a proper number of Subs and needles compared to blind Fishbone technology installation.
A combination of two techniques between reservoir simulation study to generate SOI with the new advanced completion technology called Fishbones applied on low-performance existing horizontal well is the real study integration with the final objective to increase the ultimate gas recovery in a tight gas carbonate reservoir. This is a breakthrough solution to optimize the development of tight carbonate gas fields in addition to the conventional development strategy with normal infill drillings.