bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analyzing X-Ray CT Images from Unconventional Reservoirs Using Deep Generative Models
Authors: Perez Claro Yulman , Dal Santo Niccolo , Krishnan Vignesh , Kovscek Anthony 
Published: April 2022

Abstract
Characterization of rock samples is relevant to hydrocarbon production, geothermal energy, hydrogen storage, waste storage, and carbon sequestration. Image resolution plays a key role in both property estimation and image analysis. However, poor resolution may lead to underestimation of rock properties such as porosity and permeability. Therefore, improving the image resolution is paramount. This study shows the workflow for 2D image super-resolution processes using a Convolutional Neural Network (CNN) method. The rock samples used to test the networks were three unfractured Wolfcamp shales, a Bentheimer sandstone (Guan et al., 2019), and a Vaca Muerta (Frouté et al., 2020) shale. These samples were imaged with a clinical Computed Tomography (CT) scanner (100's µm resolution) as well a microCT scanner (10's µm resolution). This established training, validation, and test data sets. The deep learning architectures were implemented in Matlab 2021b. The network performance is calculated using two metrics: i) pixel signal to noise ratio (PSNR) and ii) structural similarity index method (SSIM). In addition, porosity values on the image data sets are presented to illustrate their relevance. Training options and different strategies for network tuning are also discussed in the results section. Results illustrate the potential for AI to improve the resolution of CT images by at least a factor of 4. This level of improvement is essential for resolving fractures, other permeable conduits in impermeable shale samples, and shale fabric features. We outline a pathway to greater improvement of resolution.
Latest Technologies and Methods for Carbon Capture and Underground Gas Storage
Authors: Aydin Hakki , Yegin Cengiz , Nagabandi Nirup , Temizel Cenk 
Published: April 2022

Abstract
Carbon capture and underground gas storage technologies have been an area of significant focus in oil and gas industry over the past few decades. They reduce the carbon footprint of oilfield activities and have a critical role in the energy transition efforts by the industry. This study focuses on conducting a thorough review of literature related to latest advances in carbon capture and underground gas storage methods including real-field applications of these technologies. The future potential of these technologies in enabling the oil and gas industry to achieve its ESG goals are also discussed.
This chapter examines carbon capture and underground gas storage (CCS) technologies and summarizes various types of CCS techniques such as post-combustion, pre-combustion, and oxyfuel combustion. It describes the important operational principles, efficient methods of technology deployment, and best practices to ensure positive project economics. Additionally, the use of the CCS as a method to enable enhanced oil recovery (EOR) in the oil and gas industry, as well as application areas and challenges faced in the use of CCS in oilfield operations, are discussed. The latest advances in this technology from a global perspective and the future potential of CCS as a critical driver in helping achieve sustainability goals for the oil and gas industry are summarized.
Critical factors related to the application of the CCS, including the key decision variables to be considered while implementing projects that uses these technologies are provided to be used as a guideline in decision making. Examples of the use of these technologies to improve the sustainability of oil and gas production operations are provided, as well as the benefits, drawbacks, and challenges in scaling up the use of these technologies in fields are discussed in detail.
This study closes the gap in the literature by providing a comprehensive overview of the current status of the CCS technologies and guidelines for their implementation in oil and gas fields. It serves as a single source of information to the oil and gas industry, while laying out relevant data and information related to the CCS technologies, highlighting the latest advances in their application and the future of these technologies from a global perspective.
Prediction of Pressure and Temperature Profiles and Hydrate Formation Region in ESP-Lifted Natural Gas Hydrate Wells
Authors: Ping Xiaolin , Han Guoqing , Cen Xueqi , Bai Zhenqiang , Zhu Weitao , Peng Long , Ma Bojiaer 
Published: April 2022

Abstract
Depressurization is one of the most effective methods in natural gas hydrate (NGH) production trails. Meanwhile, electric submersible pumps (ESP) are mostly employed to depressurize natural gas hydrate reservoirs. The profiles of temperature and pressure in the wellbore have an important impact on the secondary formation of hydrate. The pressure increase caused by ESP system and the low temperature on seabed will increase the risk of secondary hydrate formation in gas hydrate production wells. In contrast, the temperature rise generated by motor and the heater added to the ESP string will decrease the risk of secondary hydrate formation. Therefore, it is necessary to evaluate the risk of gas hydrate formation in ESP-Lifted gas hydrate production wells.
Based on the world's first offshore methane-hydrate production-test system in Nankai Trough comprised of an ESP with a gas-separation system and a heater, a gas-liquid two-phase flow model coupling temperature and pressure is established to predict the formation region of hydrate in dedicated gas/water lines and mixing-delivery line. The influences of operating frequency of ESP and power of heater on temperature and pressure are analyzed in the proposed model in this research.
The results of the proposed model are verified by comparing with the first offshore gas hydrate production test in the Nankai Trough. The temperature limit for gas hydrate formation inside the well can be estimated with the proposed model and phase equilibrium model to predict the risk of secondary hydrate formation in ESP-lifted wells.
In this paper, it is demonstrated that the highest hydrate formation risk is above the discharge location of the pump and the middle and lower part of the seawater section of the water drainage line. Increasing the operating frequency of ESP and power of heater can reduce gas hydrate formation in gas hydrate wells. Besides, injection of chemical inhibitor can eliminate the risk of hydrate reformation. The results of this research can lay the foundation for flow assurance, ESP designs and production optimization of natural gas hydrate production wells.
Economic Modeling of Carbon Capture and Sequestration Projects Utilizing Re-Purposed Onshore California Wells and Infrastructure
Authors: Yang Siho , Paul Donald Lee 
Published: April 2022

Abstract
At present, approximately 37,000 out of 110,000 oil and gas wells in onshore California are classified as ‘idle’ - they have not been producing hydrocarbon or water, including EOR, for two consecutive years without abandonment. In this context, we examine whether operators retaining those current or potentially future idle wells could economically re-purpose their assets for a carbon storage operation. Such an approach would potentially defer the eventual decommissioning, abandonment, and remediation costs of these assets.
This study models the economics of a fully integrated system from source CO2 capture through subsurface storage for a thermal steam operation. The model workflow developed in this paper is as follows: capture carbon dioxide from steam co-generation plants in heavy oil steam injection fields in the San Joaquin Valley, delivering it via pipeline to selected idle producing or injection wells, converting those wells into carbon dioxide injectors, and finally injecting and monitoring for sequestration. The well re-purposing process would isolate the formerly produced hydrocarbon interval and re-complete in the overlying saline aquifer interval to be used for CO2 sequestration.
The fundamental difference of project economics between hydrocarbon production and carbon capture and sequestration is the regulatory and policy-defined financial incentives. In California, those consist of three major elements: Section 45Q tax credits by the federal government, low-carbon fuel standard (LCFS) credit by the State of California, and cap-and-trade emission allowances. The economic model shows that two factors, LCFS credit price and the cost of carbon capture systems, comprise the most significant proportion of impact on economic feasibility. To achieve the breakeven IRR of 10%, first, LCFS eligibility of the CCS project for a co-generation plant should be improved, and credit price needs to remain at least at the current level. On top of that, the expected increase in future LCFS credit prices and cap-and-trade allowance as potential revenue in an opportunity cost context would enhance economic performance. Secondly, the most plausible, the CAPEX of carbon capture systems at steam co-generation plants would need to be reduced to the lowest cost benchmarks currently seen in process plant implementations.
This paper can be viewed as a starting point to stimulate examination of carbon capture and sequestration project options by both operators managing end-of-field life producing assets, as well as State of California regulatory agencies pursuing carbon reduction as part of the state's larger energy transition strategy.
A Numerical Model Study of Scale-Dependent Fluid Flow and Storage Systems in Unconventional Reservoirs
Authors: Reichhardt David , Hoffman B. Todd 
Published: April 2022

Abstract
Unconventional reservoirs hold vast amounts of untapped hydrocarbon resources; however, given current production capabilities and our understanding of unconventional reservoir production mechanisms only 5% to 10% of these hydrocarbons are typically recovered. The ability to recover additional hydrocarbons from unconventional reservoirs is dependent on an improved understanding of the production mechanisms which are a function of the complex lithology and reservoir fluid systems, and the interactions between these systems.
The lithology and fluid systems present in most unconventional reservoirs result in production from several scale-dependent fluid flow and storage systems, or depletion systems, that combine to contribute to the total production. These depletion systems can include matrix level features defined by pore size, natural fracture systems within the matrix, and hydraulic fractures in addition to the traditional depletion systems defined by stacked pay. The fluid phase behavior within these systems also has a scale dependence that must be taken into consideration. As a result, the individual systems tend to deplete at different rates.
The purpose of this work is to describe the production mechanisms in terms of the lithology and reservoir fluid interactions. By using numerical simulation to systematically isolate production from individual depletion systems, the role and significance of each system is quantified.
A numerical model was developed to simulate the contributions to total hydrocarbon production from multiple depletion systems. Fluid tracers were placed within each depletion system to isolate the individual system production.
The results show the stage of production when each depletion system is active and the associated hydrocarbon volumes. For example, the hydraulic fracture system provides most of the initial production, but contribution from the matrix and natural fractures quickly overtakes it. Composite production curves were developed by combining the simulated production contributions from each depletion system, highlighting the influence the different systems have on the total production.
This paper provides insights into the production contributions from multiple depletion systems found in many unconventional reservoirs. Understanding the roles that the different depletion systems play on production will lead to better well spacing, reserve estimates, and improved reservoir production practices including enhanced oil recovery methods that may be optimized to target the most promising aspects of the reservoir.
Data-Driven Discovery of Physics for Reservoir Surveillance
Authors: Nagao Masahiro , Sun Wenyue , Sankaran Sathish 
Published: April 2022

Abstract
Understanding well production performance in hydrocarbon reservoirs in a timely manner is essential for closed loop reservoir management, improving operational efficiency, and maximizing value. It is desirable to have a robust and scalable method for estimating well productivity index and reservoir pressure, which can be applied in a practical and automated manner. Traditional surveillance methods are interpretive and do not scale for manual surveillance of either large fields or those with large data volumes. In this work, we propose a machine learning approach to discover physics that can be built using routine field measurements (downhole pressure and rates) and used for estimating well productivity, real-time production rates, pressure depletion and short-term forecasts.
The relationship between rates and pressure evolution is guided by nonlinear diffusivity equation. We seek methods for projecting the nonlinear state problem onto a linear (or weakly linear) space based on several methods – namely, time delay embedding, physics-inspired features, and dynamic mode decomposition (DMD). This augments the information contained in the system state with measurements of the state history. We also developed a background signal decomposition method to extrapolate routine buildup pressure data to estimate average reservoir pressure based on two different methods – optDMD (optimized DMD) and SINDy (sparse identification of nonlinear dynamics).
The background signal decomposition method was validated on several heterogeneous reservoir cases to estimate average reservoir pressure from buildup data, where our results outperformed traditional methods. In cases where multiphase flow meter rates were available, the proposed hybrid reservoir model was used to predict pressure with a virtual shut-in simulation. By offsetting the need for shutting in the well and associated production deferment, the virtual shut-in predictions were used to estimate reservoir properties. The results were validated on both pressures and pressure derivatives, typically used for pressure transient analysis. Next, we observed that the model can be used to provide accurate multiphase production rate forecasting (virtual metering) by reversing the model inputs and outputs. Based on the hybrid model, a workflow for tracking reservoir properties was developed to capture the decline of average reservoir pressure and productivity index, which was applied to both synthetic and field cases with reasonable accuracy.
The proposed hybrid reservoir modeling approach automates routine surveillance at field scale with high computational efficiency. By learning from natural operational variations continuously, it decreases planned downtime and associated production loss. It also enables detecting well performance issues much earlier to plan timely remedial actions. It provides a practical way of combining data-driven methods with our understanding of physics, while keeping the analysis interpretable and enabling closed loop reservoir management.
Evaluation of Stresses Alteration on the Productivity of Marcellus Shale Horizontal Well
Authors: El Sgher Mohamed , Aminian Kashy , Ameri Samuel 
Published: April 2022

Abstract
The objective of this study was to investigate the impact of fracture properties and mechanical rock properties on stress changes and, consequently, the productivity of a horizontal Marcellus Shale well with multi-stage fractures.
The available advanced technical information from the Marcellus Shale horizontal wells at MSEEL site provides an opportunity for an integrated analysis to gain insight into the impact of stresses changes. When the pore pressure decreases due to depletion in a reservoir, the increase in effective stress results in a reduction in fissure permeability and porosity that affects cumulative gas production. In this study, the Mohr-Coulomb model, the foremost common model, was utilized to account for geomechanical effects.
A reservoir model which incorporated the gas storage mechanisms inherent in shales, i.e., matrix porosity, natural fracture porosity, and adsorption was developed. The mechanical properties of the shale were estimated from the available well log data. The core, log, completion, stimulation, and production data from the wells located at the Marcellus Shale Energy and Environment Laboratory (MSEEL) were utilized to obtain the formation and completion properties for the model. Barton Bandis Model was then implemented in the reservoir model to investigate the closure of the natural fractures during production. The impact of the stress changes was then investigated by performing parametric studies.
The geomechanical effects such as compaction and subsidence increase as the length of the hydraulic fracture increases. Furthermore, the higher the initial hydraulic fracture conductivity is, the more significant geomechanical effects become. Both of these are the results of greater pressure depletion. Additionally, as the pressure drawdown increases (wellbore pressure decreases), geomechanical effects increase. Mechanical rock properties (Young's modulus and Poisson's ratio) also influence the geomechanical effects. As Young's modulus of the rocks decreases, cumulative gas production increases due to compaction drive.
Visualization of Liquid Slugging Using Detailed, High-Quality Pressure Monitoring
Authors: Gordon Ryan David , Ito Tokunosuke , Vekved Kerry Laverne 
Published: April 2022

Abstract
Liquid slugging in gas gathering systems is a costly problem. It is difficult to manage because it is hard for pipeline operators to know where and when slugs form and how they move. This paper demonstrates how detailed pressure measurement across pipelines in a gathering system can be used to visualize slug formation and movement, thereby enabling pipeline operators to better manage slugging issues at facilities.
Pressure monitoring devices, based on an internet of things (IoT) architecture, were installed on the main branch lines feeding the inlet separator of a gas gathering system. Each device continuously captured, stored, and delivered high-quality, time-synchronized, per-second pressure measurements to a cloud-based data service. Detailed pressure data from several days of normal operations was integrated with operational data that showed slug arrival times and volume at the inlet separator, along with timing of pigging operations. The data was assessed for correlations between slugging activity and changes in pressure patterns along each line. Pigging operations were optimized based on the results.
Clear correlations were observed between slugging events and changes in differential pressure over time along a given branch line. By recognizing the pressure pattern associated with slugging events, the location and timing of liquid slug formation in the lines of the gas gathering system were determined. Pressure patterns were distinct and could be alarmed on to provide early notification of a slugging event. The magnitude of differential pressure was found to be loosely correlated to slug size in most branch lines. The impact of pigging on pipeline operations could also be visualized as changes in pressure patterns. This visualization enabled pigging to be optimized to reduce liquid build-up in branch lines that contributed to large slugging events. The optimization resulted in a reduction in labor costs for managing slugging issues such as compressor shutdowns and flooding the inlet separator as slugging events became smaller and less frequent. It also resulted in a sustained production increase of 20% for wells feeding one of the most problematic branch lines as line pack pressure was reduced enough to impact productivity.
This case study demonstrates a new way for pipeline operators to visualize slug formation and movement in their gas gathering systems as changes in pressure along a pipeline. Once visualized, slugging can be better managed, potentially leading to production increases, reduced costs, or both. The use of detailed pressure monitoring to visualize fluid dynamics within pipes or process equipment may have many applications in the oil and gas industry for enabling operational improvements.
Eden Yuturi's Hydraulic Fracturing Evolution: Improving Well Performance from Highly Laminated Reservoirs in Ecuador
Authors: Pelaez Lauran , Calderon Diego Alberto , Fun Sang Byron Alfredo , Villarroel Lisbet Cristina , Salazar Franck , Cornejo Paul Israel , Reyes Israel , Zamora Patricio , Giol Cristian Gustavo , Grefa Maria Martina , Pozo Maria Fernanda , Lomas Jonny , Valdez Anne 
Published: April 2022

Abstract
One of the main challenges in production enhancement in mature fields is finding the optimum method to develop different reservoirs under the best exploitation strategy. Ecuador's Eden Yuturi is a mature field where nearly 15% of the field's production comes from a highly laminated, low permeability reservoir with viscous oil properties. The development of this layer requires hydraulic fracturing to economically produce the wells.
Hydraulic fracturing was implemented in Eden Yuturi in 2011. The fracturing technology has evolved since then. In 2019, the channel-fracturing technique was introduced, where proppant is pumped in pulses to achieve a heterogeneous placement within the reservoir, creating infinite-conductivity channels. The hydraulic fracture conductivity generated by open channels is higher than a conventional proppant pack. In conventional fractures, flow through proppant is described by Darcy's law; however, for an open fracture channel, the Navier-Stokes equation is applied, implying that effective permeability is 100 times higher.
Based on lessons learned for the past 6 years, some of the best practices include: perforating the entire reservoir in cluster, aggressive fracture designs averaging approximately 60,000 lbs of 20/40 proppant pumped, using resin-coated proppant to reduce proppant flowback and using ESP pumps with more robust stages that are well suited to handle solids production and viscous oil.
For the frac design, conductivity is increased from 3,500 md-ft to more than 500,000 md-ft with the channel fracturing technique. The associated dimensionless fracture conductivity increased from 2 to 50, and the resulting fracture width increased by 400%. As a result, the average fractured well productivity index increased by two-fold, resulting in higher production rates from 300 to 500 BOPD, ensuring the required volume to be economic as they decline smoothly, reaching cumulative volumes beyond 300,000 bbl of oil per well. This has enabled the Asset to increase reserves in the last campaigns by 2.5 MMbbl.
This result leads the NOC to better optimize their development strategy. Nearly 10 MMbbl are estimated to be recovered from this reservoir. Hydraulic fracturing has made the economic exploitation of this tight layer a reality since the reservoir was previously considered an uneconomic target. Through this aggressive strategy, Eden Yuturi Field has become the pioneer in economically exploiting laminated reservoirs in Ecuador.