bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Fast Predictive Models for CO2 Enhanced Oil Recovery and Storage in Mature Oil Fields
Authors: Peralta Yessica , Ganesh Ajay , Zambrano Gonzalo , Chalaturnyk Rick , Shokri Alireza Rangriz 
Published: April 2024

Abstract
Reservoir modelling tools have played a significant role in designing the subsurface fluid injection, such as CO2 enhanced oil recovery (EOR). However, these models are computationally expensive; they require extensive geological and engineering data that often are not available in the early phase of carbon utilization and storage projects. This work presents the development of fast predictive models and optimization methodologies to quickly evaluate the CO2 EOR and storage operations in mature oil fields.
Considerable experience with CO2 EOR and storage has been gained by the petroleum industry. In particular, the Weyburn-Midale project (Canada) is a comprehensive case to show how an oil reservoir could securely store CO2. Employing the Weyburn-Midale project, we developed, trained and tested several types of proxy models in multiple scenarios to assess the performance of the miscible CO2 flood in recovering residual oil, increasing the ultimate oil recovery factor while maximizing the permanent CO2 storage.
The history matching of the Weyburn-Midale CO2 EOR model involved 216 well histories (producers and injectors) from 1964 to 2006 using a compositional reservoir simulator. The predominant exploitation scheme was based on an inverted nine-spot pattern waterflooding, water alternating CO2, and consequently CO2 injection. Two simulation data sets were employed at different periods of 1956 through 2006, and 2007 through 2025. Among several proxy models, an artificial neural network (ANN) model proved to accurately estimate features of interest, namely fluid production (oil, water, gas), fluid injection (water, CO2) and the amount of CO2 stored in the reservoir. Additionally, an autoregressive exogenous input (ARX) model was implemented to predict the future outputs in response to a future input. Inspection of the relative estimation error and the model fitness score showed that the proxy model was capable of rapidly reproducing the trend in the validation set satisfactorily. Lastly, we evaluated the transfer of learning from a proxy model, trained to the Weyburn-Midale field (Canada), to assess the performance of CO2 EOR in another mature oil reservoir in Europe (Romania).
The application of proxy models under geological and operation uncertainties offers huge reduction in computational time and engineering data requirements. The results from the Weyburn-Midale case study deliver critical insights into the analysis of many process factors and modeling techniques intended to assess the economic limits and long-term performance of CO2 EOR and storage in mature oil fields.
Mitigation of Vortex-Induced Vibration in Offshore Structures
Authors: Majumdar Ananya , Adhikary Biplab Ranjan 
Published: April 2024

Vortex-induced vibration (VIV) study of any offshore structure is of paramount importance to check the structural stability. VIV poses a significant concern for these structures, as the excessive vibration can lead to fatigue damage and structural failure. Mooring lines, risers, pipelines, and other attachments can also get damaged in case of offshore structures. When the shedding frequency approaches the structure's shedding frequency, these vibrations can be major and perhaps dangerous. VIV can occur at low as well as high Reynold's number regime. Because of rising demand for crude oil, offshore gas, and oil, exploration has been shifted to deeper sea levels. Offshore floating wind turbines are used to conserve energy and generate electricity. It can further help to reduce visual pollution and achieve stronger and more constant winds. Floating offshore wind turbines are considered a viable solution in ocean depths more than 50 to 60 meters and with significant wind resources. As an emerging technology, it can utilize less foundation material, shorten the installation and decommissioning times, and create more wind energy. New dangers can be mitigated by employing commercially available bottom fixed turbines and well-known oil and gas technologies for floaters.
VIV can cause large-amplitude vibrations of tethered structures in the ocean. Thus, the effect of VIV on floating structures needs to be studied.
The flow-induced response of a floating structure is generally checked for crossflow. In this study a response reduction technique is proposed based on the in-house modelled two-way coupled interaction of fluid and structure due to vortex-induced motion.
Revolutionizing Offshore Installation and Terminal Manager Emergency Response Training and Assessment: An Innovative, Cost-Effective, and Global Solution for Competency Sustainment
Authors: Wijaya Hendrik A. , Yusof Yushafidi Bin , Bawan Mohd Zainuri Bin , Idrus Hana Maslinda Binti Md 
Published: April 2024

Abstract
In response to the challenges posed by the COVID-19 pandemic, this paper unveils a pioneering emergency response training and assessment framework tailored for Offshore Installation Managers (OIMs) and Terminal Managers (TMs). Focused on the development and deployment of an innovative remote simulation system, the objectives of this program extend beyond the initial constraints of the pandemic, evolving into a best practice model. The paper expounds on the cost-saving benefits of the system, its successful extension to facilities in Malaysia, Iraq, and Turkmenistan, and the establishment of a centralized training hub in Malaysia.
The methodology involves a systematic approach that includes the design, development, and deployment of a cutting-edge online simulation system. This system replicates diverse emergency scenarios, including helicopter crashes, work boat collisions, tank fires, bomb threats, and other incidents outlined in emergency response plans. Centralizing training in Malaysia while engaging participants globally, the program ensures command and control training, fostering competency in managing major emergencies.
The results showcase the effectiveness of the program, with substantial cost savings and sustained high-quality training for OIMs and TMs. Implementation across diverse regions, with assessors and directors operating remotely from Malaysia, underscores the scalability and efficiency of the approach. Real-life situations attest to the preparedness and effectiveness of offshore and terminal leaders in command and control.
In its contribution to the petroleum industry, this paper introduces a cost-efficient and sustainable emergency response training and assessment program. The unique online simulation system, coupled with a centralized training hub, not only reduces costs but also minimizes the carbon footprint, ensuring consistent quality across geographically dispersed facilities. By detailing the successful implementation of this program, the paper enriches the existing literature, providing a blueprint for organizations aiming to enhance the readiness of their leadership in responding to emergencies.
Improving Drilling Performance Through Intelligent and Automated Operating Parameter Planning
Authors: Chen Wei , Hiep Nguyen Tien , Zhang Zhengxin , Shen Yuelin , Scarioni Franklin Linares , Vasquez Daniel Cardozo , Gonzalez Luis Felipe , Skoff Greg , Arevalo Yezid , Converset Julien 
Published: April 2024

Abstract
Drilling operations are subject to drilling dynamics dysfunctions like bottom hole assembly (BHA) shocks and vibration (S&V) that can lead to premature downhole tool failures, poor hole quality and reduced rate of penetration (ROP). This is addressed by domain experts by selecting optimum drilling parameters based on their knowledge and offset performance. A hybrid approach was developed that blended machine-learning algorithms and domain knowledge to automate and improve the design of an optimum operating window for the best drilling parameters (weight-on-bit (WOB), top drive rotary speed (RPM) and flow rate) using historical offset data. The philosophy for optimum operating parameter intelligent planning is based on evolution and continuous learning from historical data. The workflow for the hybrid approach begins with the automated selection of offset well data, then an algorithm is used to align data by formation tops and automatically detected drilling zones which enables parameter statistics evaluation along the depth of the subject well. Based on offset well S&V data and computed mechanical specific energy (MSE), a machine-learning algorithm is applied to divide the intervals into drilling zones, such as benign drilling zone, hard stringer zone, interbedded zone, and severe S&V zone. When the optimum operating window is generated, more aggressive parameters are explored for benign drilling zones to maximize ROP, whereas for the other zone types, the best parameters are automatically identified through the usage of sweet spots in self-generated S&V heatmaps in offset wells. If no stable operating window is found in the heatmaps, domain mitigation logics are used based on the observed S&V modes (axial, lateral, or torsional) in offset data. The parameters’ roadmap is then executed and monitored in real-time, and the post-run data are collected to feed into another evolution cycle for continuous learning and improvement. We implemented this intelligent parameter planning workflow into a mature drilling data analytics platform for deployment to domain users. It was used by drilling engineers in four different drilling environments for field testing to replace the legacy manual drilling roadmap preparation process. Considerable time savings have been reported for offset well data collection and analysis for parameter roadmap generation. More importantly, jobs executed with the new roadmaps have demonstrated reduction in both drilling time and downhole dysfunctions. In this work, we leveraged data analytics, domain knowledge, and physics and machine-learning models to generate a depth-based optimum operating parameter roadmap automatically. This workflow enables ROP improvement and the reduction of drilling risks, becoming a key element for the evolution of autonomous drilling operations and well cost reduction.
Decarbonization Through Reducing Energy Losses in Water Injection Systems: Mechanical Degradation of Drag Reducers in Friction Loops Testing
Authors: Al Moajil A. M. , White R. , AlRustum A. 
Published: April 2024

Abstract
Drag reducing agents (DRAs) are used to reduce friction created by turbulence flow in water transport and injection systems. The objective of this paper to assess mechanical degradation of rigid and flexible polymers used drag reduction applications.
Commercial synthetic polyacrylamide-based DRA and CMHPG polymers were obtained. Synthetic brine was prepared to simulate typical water in surface pipelines. Friction loop test was used to assess friction reduction at various conditions, testing modes, and DRA polymer concentrations.
Mechanical degradation of flexible and rigid polymers for drag reduction application was assessed. TGA analysis indicated the activity of the polyacrylamide polymer was 29 wt%. Viscosity measurements indicated ammonium persulfate reduced the viscosity of 1000 ppm polyacralamide-based DRA by 41 and 36% at 25 and 40°C, respectively. Flow loop testing showed that the flexible polymer was mechanically degraded (i.e. DR’ &lt; 0.1) within 15, 47, and &gt;200 min at 12 gal/min, NRe 70,022, 75°F, at reservoir tank bypass flow mode using 150, 300, and 1000 ppm of the PAM-based DRA, respectively. Rigid polysaccharides-based drag reducing agents showed significant resistance to mechanical degradation compared to polyacralamide-based DRA. Mechanical degradation of the polymer (via chain scission) was mainly caused by shearing/turbulence flow, circulation pump, number of flow cycles, and time. The degradation rate depended on DRA concentration, flow rate, polymer type, and circulation flow mode. DRA injection is a viable alternative to increase production capacity and/or improve energy efficiency.
A Pioneer Step in Restoring Well Integrity of Extreme Sour Well Through End to End Workover Optimization Utilizing Lean Methodologies
Authors: Al Omairi S. M. 
Published: April 2024

Abstract
Yibal Khuff (YK) is a highly sour oil field located in the North of Sultanate of Oman. During Production phase, pressure builds up the annulus behind production tubing resulted in integrity failures, where wells workover required. This paper demonstrates how the operator successfully reduced the planned intervention time by 60 % and restore wells back to healthy production. The paper will also explain how engineering enhancements and innovative Lean methodologies were used for efficiency optimization.
Lean Project (LP), an innovative continuous improvement-based approach; was re-structured to address end to end (E2E) workover challenges. The Project stakeholders management consisted of utilizing Suppliers, Inputs Process, Outputs and Customers (SIPOC) which included identification of main stakeholders, assessment of impact and Voice of Customers (VOC). Value Stream Mapping (VSM) exercise was done for the workover and resulted in list of waste and opportunities to optimize the process. VSM allowed for visualizing the end-to-end process and optimize Process Cycle Efficiency (PCE). Root Cause Analysis (RCA) was conducted using the "5 Whys" method. Moreover, countermeasures were assessed and designed to be deployed.
After piloting the suggested solutions with required controls in place, and because of LP countermeasures, a 60% reduction in planned operation time and 54% cost saving have been observed. This was achieved by eliminating the un-planned change in well sequence which eliminated 62.4 hours of operational downtime through developing fit per purpose sequence procedure. Combining Casing scraper and polish mill in one run saved 98.64 hours compared to planned phase duration. Optimization of operational steps reduced the Gap to Potential (GtP) time by 60% and eliminated Invisible Lost Time (ILT). In addition, the process was reflected in a Standard Operating Procedure (SOP) to be used and replicated across YK field. Finally, the SOPs that were developed on this project supported the local cluster in minimizing oil deferment by reducing the duration of hoist workovers and by raising the cluster's integrity compliance to a near-perfect record.
This paper will give a brief about the application of Lean thinking methodology in a large Omani operator and how the LP tool can help identify and solve day to day problems within well interventions. The LP technique was used for the first time to optimize high sour high risk workover processes. Tools including, stakeholder engagements, root cause analysis and value stream mapping will be explained in this paper in more detail.
Lessons from a Year-Long Operation of an Atmospheric Pressure Flare Gas Recovery System
Authors: Al Kalbani H 
Published: April 2024

Abstract
As the world approaches the 2030 deadline set by the World Bank to eliminate routine flaring, substantial investments are directed towards establishing flare gas recovery, treatment and export infrastructure. This paper delves into the critical components of this imperative task: isolating the flare system and implementing a gas recovery system. The objective is to distill valuable insights and lessons learned from our year-long experience operating such a system, providing a valuable resource for future projects. The lessons learned encompass concept development, design considerations, commissioning procedures, and essential operational aspects. These lessons cover a broad spectrum of critical considerations, including compressor selection, process design fundamentals, control, startup & shutdown sequences, commissioning procedures and underscore the paramount importance of comprehensive training protocols.
The flare gas recovery project aimed to capture gas from atmospheric pressure (AP) sources within the plant. The AP flare gas network intricately collects atmospheric gas from diverse sources, including free water knockout tanks, skim tanks, buffer tanks, drain vessels, skimming vessels, purge gas, and more. The project installed an efficient isolation system which directs this gas to the newly installed gas recovery compressor, where the gas is compressed before being sent for further treatment.
Compressor selection was a crucial decision, and the project ultimately chose the rotary vane compressor due to its exceptional robustness in handling wet gas. Determining the compressor's flowrate entailed a meticulous process, factoring in operational dynamics, site-specific conditions, and gas flashing considerations.
Implementing the control schematic was equally careful, given the challenge of low suction pressure. Careful placement of pressure transducers ensured adequate volume at compressor suction to prevent pressure spikes triggering frequent shutdowns. The isolation system incorporated both an emergency shutdown valve and a pressure control valve, designed to re-route gas back to the flare when necessary
The start-up sequence was thoughtfully designed to meet the dual requirements of isolating the flare while preventing back pressure in the connected tank until the compressor was in operation. Similarly, the shutdown sequence was carefully engineered to prevent the compressor from running while the flare emergency shutdown valve was open. Rigorous commissioning involved using fuel gas to validate the control scheme's functionality, ensuring it operated as intended.
Training considerations were integral from the project's inception, incorporated into design reviews and Hazard and Operability Studies (HAZOPs) and upheld during commissioning. In summary, our experience underscores the indispensable role of meticulous planning, technology selection, and comprehensive training in realizing efficient and environmentally responsible gas recovery project.
Using Casein Peptone as a Sustainable and Natural Solution for Mitigating Gas Hydrate-Induced Flow Assurance Challenges in Natural Gas Pipelines
Authors: Singh A. , Suri A. 
Published: April 2024

Abstract
Casein peptone efficacy as a hydrate inhibitor is investigated, as is its potential for synergy with two eminent kinetic hydration inhibitors (KHIs), polyvinylcaprolactam (PVCap) and polyvinylpyrrolidone (PVP), to improve hydrate inhibition performance. The induction time (IT) / hydrate formation delay time and the average hydrate growth rate (AHGR) post-hydrate formation at concentrations of 0.25 wt%, 0.5 wt%, and 1 wt% of casein peptone were evaluated for methane gas at 7.6 MPa, with a hydrate equilibrium temperature of 10.45°C. 1°C/h constant cooling rate is used in the hydrate formation tests.
The individual effectiveness of casein peptone, PVP, and PVCap is evaluated. The synergy between common KHIs (PVP and PVCap) and casein peptone is assessed by creating 1:1 blends of casein peptone with PVP and PVCap, with the individual performance of PVP and PVCap at an equivalent total inhibitor concentration (KHI + synergist and KHI) for a fair comparison.
Casein peptone is found to have a promising hydrate inhibiting performance in the study. At similar concentrations, it outperformed the conventional KHI PVP40K, demonstrated similar efficacy to the conventional KHI PVP10K, and exhibited only slightly lower performance than the conventional high performing KHI PVCap 40K. This finding highlights the potential of casein peptone as a viable alternative to traditional KHIs, particularly for offshore locations where environmental concerns are a priority. The ability of casein peptone to inhibit hydrate formation at levels comparable to existing conventional inhibitors, coupled with its natural origin and biodegradable properties, make it an attractive candidate for future research in the field of deep-sea hydrate risk management.
AI-Assisted Automation of Well Type Selection and Pad Optimization During Well Placement in Yan'an Tight Gas Reservoir
Authors: Wang Xiangzeng , Zhang Longjun , Song Jiaxuan , Zhang Ping , Lin Jin , Liu Yunlong , Zhang Jianfeng , Zhang Lei , Qiao Xiangyang , Liu Peng , Wang Kai , Xie Xiaofei , Zhang Le , Ye Dongqing 
Published: April 2024

Abstract
The Yan'an tight gas field, situated in the Ordos basin in central China, is emblematic of a typical tight gas reservoir. The field's development planning has been confronted with numerous challenges arising from conditions characterized by high geological heterogeneity, low porosity, multiple production formations, low lateral sand continuity, and a complex topography. Among the pivotal tasks in field development that necessitate addressing these challenges are the screening of well types and the optimization of pad locations. The judicious selection of well types, including horizontal, deviated, or vertical wells, in conjunction with the optimization of pad locations, not only facilitates the control of reserves on a larger scale but also significantly diminishes well construction costs. Conventionally, the manual determination of well types and the optimization of well pad locations rely on the analysis of 2D maps depicting sand distribution and other geological properties. This conventional approach heavily depends on individual experience and meticulousness, requiring weeks or even months to reach a final decision, with results that may lack consistency.
To address the aforementioned challenges, two algorithms have been developed, harnessing both domain expertise and a state-of-the-art machine learning (ML) algorithm. The first algorithm concentrates on well type selection based on considerations such as well targets, geological conditions, and drilling constraints. A heuristic algorithm, in conjunction with the nearest neighbors method, has been devised to identify optimal combinations of various well types with the least number of wells. The second algorithm focuses on optimizing well pad locations, taking into account surface, drilling, and cost constraints, using a modified K-means clustering method tailored to address real problems under diverse conditions. Through the implementation of these developed algorithms, the planning of hundreds of infill wells in the Yan'an tight gas field has been achieved with minimal human involvement in as little as half a day, in contrast to the traditional timeline of months. The developed algorithms serve to significantly enhance well placement efficiency, reduce operational expenditures, and consistently yield reliable results.