bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Study of High Energy Materials Used as in-Situ Heat Generation for Offshore Heavy Oil Thermal Recovery
Authors: Lin Tao , Li Tianliang , Song Hongzhi , Han Rui , Gu Qilin 
Published: February 2024

Abstract
Thermal recovery technology is the development of the most effective way, including CSS, Flooding and SAGD, which can effectively solve the problem due to the high viscosity of heavy oil and poor mobility. However, it is difficult to recover heavy oil commercially and efficiently using conventional thermal recovery technology for offshore oilfields. That is because the limited platform area and sea water, which is commercial and easy for onshore fields. Downhole chemical thermal technology is widely used in heavy oil thermal recovery home and abroad. However, it is more used in plug removal, well bore hot washing and so on, because of its limited heat release. Due to its own advantages, high-energy material is suitable for application in heavy oil thermal recovery. Combined with the requirements of offshore oil field, high-energy material A is selected. Moreover, the heat released by the mixed reaction of agent A and agent B is used to heat the formation heavy oil, by the way of laboratory experiment and reservoir engineering calculation combined. N2 and CO2 are generated during the reaction, which reduces the viscosity of crude oil and replenish formation energy. The laboratory experiment results show that the high-efficiency chemical thermal reaction exotherm exceeds 1500 kJ/mol, which is three times that of the conventional chemical thermal reaction (300-400 kJ/mol), and no catalyst is needed. The method for controlling the rate of exothermic reaction was obtained by the research on influence factors such as salinity, solute concentration and pH. Reservoir engineering calculation results for 2 heat injection wells in a specific target block of Bohai Oilfield show that the cost can be reduced obviously. Meanwhile, agent A and agent B can be configured as an aqueous solution. The injection process is simple and the construction is convenient. This technology can be used in both huff and puff and flooding process as downhole thermal recovery. Moreover, it can be conducted in separate horizontal production wells as huff and puff, or it can be used in double horizontal well injection-production, five-spot pattern or other injection-production well pattern as WAG flooding. The injection process is simple and the construction is convenient. It is also suitable for processes such as wellbore cleaning, plug removal, thermal recovery auxiliary process and thermochemical stimulation in medium-deep heavy oil fields and offshore oil fields. It has a broad application prospect.
Impact of Impurities in CO2 Fluid to Carbon Capture, Offshore Pipeline Transportation and Sequestration Topside Facilities Design During Feasibility Study
Authors: Nazori Qurratuaini Muhamad , Hamdan M Rafiq Bin , Shaharom Murni , Yusoff Zuriyaty , Amirrudin Farahnajwa , Hashim Wan Mahsuri Wan , Anuar Astriyana , Ali Zalina 
Published: February 2024

Abstract
A depleted gas reservoir field located offshore Malaysia has been identified as a Carbon Dioxide (CO2) sequestration site to dispose inherent and post-combustion CO2 from domestic and foreign sources to achieve significant reduction in carbon emission for a more sustainable future. One of the key success criteria for the Carbon Capture and Storage (CCS) development is transporting and injecting CO2 fluid into the reservoir throughout field injection life. Pipelines were identified as the primary means of transporting CO2 from the capture source to the sequestration site. Transporting CO2 fluid in a 200km pipeline can be incredibly challenging due to varied CO2 fluid composition and the uncertainties in predicting CO2 fluid thermodynamic behavior. Type of impurities and Equation of States (EoS) selection will impact the thermo-physical properties of CO2 and must be considered in the design and operation of topsides facilities and pipeline. Due to uncertainties and limited data available during feasibility study, some assumptions were adopted to perform pipeline flow assurance study. This is necessary to determine the design requirement for an onshore CO2 gathering hub, compression system, pipeline and injection facilities which will be used to establish feasible operating envelope.
This study adopted a comprehensive workflow to perform CO2 pipeline flow assurance study during feasibility study to ensure any uncertainties and optimization strategies were considered at the early stage of CCS development. CO2 fluid modelling was performed considering the impact of impurities to CO2 fluid phase behavior and its thermophysical properties. Thermodynamic predictions from several EoS were evaluated prior to EoS selection. The selection of a suitable EoS is necessary to ensure robustness of the proposed design and operating strategy.
During feasibility study, several key data is undefined or uncertain. Hence a range of data and sensitivity evaluations were adopted in performing the thermohydraulic analysis. Engineering margins were proposed to provide conservatism to ensure robustness of the design envelope to meet project deliverables. As the project progresses and more reliable data is made available, the overall design can be refined and further optimized.
This paper will focus on comprehensive workflow for purpose of developing the design operating envelope and defining the recommended methodologies and EoS to be used to perform CCS topsides and pipeline design during feasibility stage to ensure any uncertainties and optimization strategies were considered at the early stage of CCS development.
Knowledge-Guided Machine Learning Method for Downhole Gauge Record Prediction in Deep Water Gas Field
Authors: Zheng Haiyan , Lin Botao , Jiang Jie , Jin Yan , Peng Long 
Published: February 2024

Abstract
A 1500-meter deepwater gas field in the South China Sea consisting of several wells has been installed with permanent downhole gauges (PDGs) to monitor downhole pressure. However, the high-temperature and high-pressure conditions pose a significant risk of PDG failures during the first few years of operation, which are prohibitively expensive to repair or replace. Therefore, it is essential to develop efficient models that can provide accurate estimations of the bottomhole pressure.
In this paper, we proposed a method for predicting downhole pressure by integrating physics-based models with machine learning models. First, with the historical temperature and pressure data collected from the wellheads and the PDGs, a physics-based model was built on the basis of the wellbore multi-phase flow theory to depict the gas-liquid pipe flow behavior. Afterward, machine learning methods, XGBoost and Feedforward neural network were utilized to build data-driven model for predict bottomhole pressure. Finally, based on these two models, a knowledge-guided machine learning (KGML) model that integrates the physical knowledge and the data-driven model was established to predict the bottomhole pressure. The domain knowledge from the physics-based models was incorporated into the loss function as an adaptive weight such that the physical constraints were enforced during training.
Based on the real-world data collected from two wells of the deepwater gas field in the South China Sea, a set of experiments were carried out to evaluate the proposed method for downhole pressure prediction. Compared to the pure data-driven model, the KGML model significantly reduces the distribution shift bias in pressure, improving the Mean Absolute Percentage Error (MAPE) of the pressure prediction by approximately 50%. Therefore, the KGML model can quantitatively describe the complex relationship between the wellhead temperature or pressure data and their downhole counterparts. Moreover, KGML exhibits robust performance across different well pads in the gas field, implying its extensibility to address the PDG failure challenge in a variety of deepwater gas wells. Consequently, the model can provide an efficient and economical approach for downhole measurements in deepwater regions.
CO2 Solubility in Brine Aquifers – Volumetric Considerations
Authors: Pedersen K. S. , Christensen P. L. 
Published: February 2024

Abstract
A thermodynamic model concept and model parameters are presented for predicting the solubility of CO2 in pure water and in water with one or more of the salts, NaCl, KCl, CaCl2 or MgCl2. A cubic equation of state with a non-classical mixing rule is used to describe the mutual solubility of CO2 and H2O. Classical mixing rules with a temperature-dependent binary interaction parameter are used to describe the interactions between H2O and salt ions and between CO2 and salt ions. A good agreement is seen with the experimental data for the CO2 solubility in brine. The solubility of CO2 in brine is important when assessing the possibilities for storing CO2 in saline aquifers. The presence of salt in an aqueous solution reduces the solubility of CO2 by 2.5-3% for each weight% of salt added. Very large amounts of water are required, if a considerable part of the CO2 produced by combustion of oil and gas is to be stored and dissolved in saline aquifers. For example, it takes approximately 50 m3 of water to dissolve the CO2 produced by burning 1 reservoir m3 of oil.
Fracture Parameter Inversion in Geothermal Reservoir Using Deep Learning
Authors: Sun Shibo , Wang Wendong , Su Yuliang , Deng Yuxuan , Li Haoyu 
Published: February 2024

Abstract
Proper characterization of fractures is critical for evaluating the effectiveness of fracturing jobs and optimizing well performance in geothermal energy production, unconventional reservoirs, and other areas. However, accurately determining the size, shape, and orientation of these fractures solely from microseismic events is challenging due to weak signals and noise. To address this challenge, this study proposes a novel workflow that directly builds accurate fracture models from microseismic events using the DBSCAN clustering algorithm and BiLSTM-ESMDA. The first step is to filter the noise in microseismic events using the DBSCAN clustering algorithm. Next, a 3D planar equation is employed to construct the fracture plane in each perforation segment. Based on the results of this step, reservoir simulations are performed iteratively using PEBI grids and a BiLSTM surrogate model. Multiple representation models are obtained to capture calibration uncertainty and enable subsequent studies of long-term well performance, such as history matching for production. Finally, the ES-MDA history auto-fitting algorithm is utilized to find the most appropriate fracture model for matching production data through iterative processes. The developed inversion method was implemented on a representative geothermal model with a complex fracture network. The results demonstrate that the DBSCAN clustering algorithm effectively reduces noise in microseismic activity and ensures the accuracy of fracture geometry. A large number of different fracture models can be quickly generated by the surrogate model to capture calibration uncertainty. ES-MDA is utilized to optimize the fracture model and identify the optimal solution. The fracture models constructed using this method exhibit fracture half-lengths that are 20%-30% smaller than those estimated by microseismic monitoring. Furthermore, the high level of historical fit for this horizontal well indicates that the complex fracture model is realistic for the mine site. This study introduces a new approach to building a complex fracture network. By using microseismic data and BiLSTM-ESMDA, this method provides a practical solution. The proposed workflow significantly improves the accuracy of fracture network prediction and computational efficiency compared to traditional fracture inversion methods, which are often plagued by high multi-solution, high computational cost, and difficulties with convergence.
CCS Vs Hydrocarbon - Similarities and Differences, A Geological Perspective
Authors: Lee Charlie , Tucker Owain , Seevam Patricia 
Published: February 2024

Abstract
Carbon capture and storage (CCS), a safe and proven technology, is a key part of a portfolio of solutions for CO2 emission reduction, estimated to account for 6-20% of CO2 reduction needed by 2050 (IEA, 2014; IPCC, 2018). The geoscience community in the Petroleum Industry plays an important role in the evaluation, exploration and appraisal of geological CO2 storage sites, especially given similarity in the key subsurface elements required in both CCS and Hydrocarbon.
CO2 System Water Solubility and Water Condensation Rate Modelling for Pipeline Integrity Management
Authors: Chen D. , Lim L. T. , Pottayil A. , Sørensen H. 
Published: February 2024

Abstract
In carbon capture and storage (CCS) projects, the fluid streams typically contain various impurities such as H2, N2, CO, Ar, O2, H2S, CH4 and also water. When it comes to transporting CO2 through pipelines, it is crucial to investigate the potential risks associated with hydrate formation and corrosion. These investigations often rely on the use of software modeling tools, and ensuring the accuracy of the model's parameters is of utmost importance. Key model parameters in relation to hydrate and corrosion risk include water solubility and hydrate dissociation temperatures. The accuracy of the modelling results would ultimately depend on the selection of the appropriate Equation of State (EOS) and polar model combination. This study shows how the optimal EoS model can be selected by comparing CO2 saturation pressure and solubility calculations, as well as hydrate formation temperatures, with various experimental data. This could lead to the selection of the most suitable EoS models and allow engineers to quantify the safety margin in a more effective manner. In addition, simulations were conducted to determine water solubility limits for CO2 rich fluids with various levels of impurities, providing insights into the distinct impact of each impurity has on water solubility. The impact of impurities and various design and operating factors on free water drop out along pipeline were demonstrated via a CO2 pipeline transportation case study. A separate depressurization study using a transient simulation was carried out to better understand the hydrate formation potential in such undersaturated CCS systems. In particular, the selection of most suitable EoS for CCS applications was discussed. Through this analysis it was possible to highlight the strength and limitation of various models which offers a new dimension in selecting the appropriate model.
Applicability Analysis and Mechanical Characteristics of Deep Water Suction Pile
Authors: Xu Dongsheng , Fan Jianchun , Yang Jin , Zhang Tianwei , Zhu Chunlin , Sun Ting , Zhou Yingfang , Liu Xun , Zhao Yuhang , Zhu Hong 
Published: February 2024

Abstracts
The seabed soil in the deepwater surface has the characteristics of soft soil and low bearing capacity, the suction pile has the characteristics of high bearing capacity, it has broad application prospects in deep-water oil and gas drilling and production. Through the test experiments of lateral bearing capacity of suction pile after installation in place and numerical simulation of maximum stress and maximum displacement of suction pile wellhead, it is found that the bending moment load will cause the suction pile to be offset, and with the increase of the bending moment load, the wellhead offset increases, and the gasketed end shifts downward; with the increase of the tilting angle of the suction pile, the maximum transverse displacement and the maximum stress of suction pile increase, and the suction pile can protect the conductor from deformation effectively. Deformation. This study can be an important reference for the construction of wells with suction piles in deep-sea soft ground.
Multiphase Virtual Flow Metering: A Step Change in Production Management
Authors: Mishra Shaksham , Karanjkar Parag , Rawat Devina 
Published: February 2024

Abstract
A multiphase flowmeter capable of adapting to varying well conditions and providing reservoir transient data is an essential tool for reliable production planning and optimization. This is the main driver for the development of a multiphase virtual flow metering (VFM) module, which is intended to be an add-on to the traditional production management system, (PMS), and as a value addition for the operator.
Current physical flow metering systems have certain limitations such as a need for extensive calibration, and high capital and maintenance costs. Also, simultaneous monitoring of every producing well can be cost-prohibitive; thus, making it difficult to determine the field production efficiently and accurately. Having limited real-time field data adds a high degree of unreliability to any simulator predictions. The PMS integrated multiphase VFM described in this paper has been designed to specifically address some of these concerns in a cost-effective manner. This VFM system operates on simulated data sets as well as live field data, which are obtained at a much higher frequency to capture even short-duration transients in the field. An additional advantage of this system is that it can be deployed individually for each well, which facilitates single-well production metering.
The VFM module, based on the dynamic multiphase flow simulator, has been developed by one of the industry leaders in simulating transient behavior of flow from a reservoir through the pipeline system. Virtual results such as pressures, temperatures, and multiphase flow rates from a digital-twin of the field are used as base results to predict the field flow rates. These predicted flow rates are compared with real-time data from instruments along the well tubing at the bottom-hole and wellhead. The VFM module processes deviations between predicted and real-time data, adjusts for factors such as instrument sensitivities and field data quality, and corrects the virtual flow rates even further towards more accurate predictions. To validate and confirm this, the model also outputs the confidence rating associated with the improved predictions.
These predicted results and associated confidence levels are the final outputs from the VFM system. When integrated with the PMS, this VFM module can also configure alerts to the user in the case of any sudden risks or unwanted transients arising from the reservoir such as water breakthrough in a gas well. Upgrading the PMS with the new VFM module will empower the operator with reliable and accurate flow predictions and help overcome the production flow rate uncertainty In addition to removing dependency on field instrumentation, this VFM module will facilitate improved field production forecasting, and can help lead to timely intervention in potential production-loss scenarios caused by unexpected transients.
Numerical Study of the Crosswind Effect on Booster Compressor Cooler Fan Performance for the Wellhead Platform
Authors: Thannit S. , Pittayaporn G. 
Published: February 2024

Abstract
The wellhead booster compressor (BC) is a crucial machinery component utilized for pressure recovery in production. In Greater Bongkot North field (GBN), the wellhead BC package phases 5 and 6 have smaller cooler fans than other phases. It makes them frequently to be tripped by engine jacket water (EJW) temperature high during strong wind due to crosswind interference occurs. Consequently, this impedes the BC fan cooler from operating at its full capacity, resulting in inadequate heat transfer of the engine. This study analyzed the influence of crosswind on the performance of BC cooler fans with an optimal design wind barrier type by using numerical modeling or computational fluid dynamics (CFD). The simulation results showed that the crosswind has a negative effect on BC cooler fan performance. At all crosswind speeds, the results showed that the wind barrier 30° deflector type is the optimal barrier design to improve BC cooler fan performance on the wellhead platform from the effect of the crosswind.
Impact of Silica Blend Towards Early Compressive Strength Development of Well Cement Class G
Authors: Ashraf Shameed , Bogaerts Martijn , Mohanaraju Haresh 
Published: February 2024

Abstract
In this paper we evaluate the effects of silica on early compressive strength development of well cement Class G during the first 24 hours. The paper’s scope is a 15.8 lbm/galUS system with 35% by weight of cement (BWOC) silica varied between fine, medium, and coarse grades, followed by an optimized version. The addition of silica at 35% BWOC is an accepted industry norm for exposure of 110°C or greater. Slurries are evaluated at 120 and 160°C by an ultrasonic cement analyzer (UCA) to determine the compressive strength development.
API 10A compliant class G cement is added with different grades of silica with an average size of 4.5 µ (fine), 16 µ (medium), and 330 µ (coarse) at 35% BWOC separately. It is mixed according to API RP 10B-2 and the compressive strength development is evaluated using the ultrasonic cement analyzer (UCA) at 120 and 160°C. The time taken to reach 50 and 500 psi, together with the strength value at 12 and 24 hours, are compared for differing silica grades. The slurry’s rheological behavior is evaluated to eliminate unfavorable slurry properties due to silica size.
Testing shows that silica size is a significant contributor to the early compressive strength development. The fine silica slurry achieved higher strength development compared to medium and coarse silica. The drawback is that the use of a fine product alone causes unacceptable high slurry gel strength. An optimized silica blend being a mixture of the three grades provides the highest compressive strength development and favorable rheological property. At 120°C, the coarse silica alone has the lowest strength at 24 hours, while the medium-sized silica provides a 49% increase over the coarse grade. The fine grade provides a 67% increase over the medium grade. The optimized silica blend can provide an additional 7% increase over the pure fine-grade silica. An evaluation done at 160°C shows that course silica provides the least compressive strength while the medium silica provides about six times the value of the medium, and the fine about 5% more than the medium. The optimized silica blend provided an additional 5% over the fine grade.
Although the industry is clear about the need to add a minimum 35% BWOC of silica to prevent strength retrogression for high-temperature applications, there is little information on how silica grades affect the early compressive strength development of the cement system. This study has clarified that proper optimization of silica grades can bring out the best early compressive strength for elevated temperature applications.