bluuebunny/crossref_metadata_2025_split huggingface dataset:
Horizontal Coal Seam Gas Well Orientation Optimization: The Impact of Stress Regime
Authors: Saber Erfan , Qu Qingdong , Aminossadati Saiied M. , Chen Zhongwei 
Published: October 2022

Abstract
Horizontal boreholes have been routinely applied to coal seams as a cost-effective way to maximize coal seam gas production. However, these wells can encounter severe instability issues during field development due to significant horizontal stress loss and change in deviatoric stresses acting on the borehole. In this work, a general dual-porosity dual-permeability model is established and assigned to a coupled gas flow and coal deformation numerical model to investigate permeability change and borehole break-out regarding different in-situ stress regimes around a horizontal borehole. Mohr-Coulomb failure criterion is used in this model.
The results show that drilling parallel to the maximum horizontal stress direction neither achieves the best stability of the borehole nor maximizes the permeability ratio. Drilling along the minimum horizontal stress direction would maximize the permeability ratio, but it has the worst stability. The optimal drilling direction window considering both permeability ratio and borehole stability is recommended to be between 45– 60°.
Novel Feature Augmentation and Input Reshaping Strategy for Accurate Seismic-Based Elastic Property Prediction Using Deep Learning
Authors: Law May , Jaya Makky Sandra , Jones Ernest Austin 
Published: October 2022

Abstract
Data limitation and sparsity are considered the main source of non-uniqueness and ill-posedness in elastic property prediction on seismic data using Deep Learning (DL). The ill-posed regression problem can be solved by conducting adequate pre-processing steps through data augmentation, feature engineering and feature selection. In this paper, we develop a novel technique of reshaping the input data into various multi-dimensional shapes before using the data as an input for the DL model. This strategy can increase the spatial context and temporal data coverage which is important for regularizing the DL model during training process. We also investigate the model performance between a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN), specifically the Long-Short Term Memory (LSTM) architecture on 2D synthetic seismic data. Our findings show that using the newly developed feature augmentation and input reshaping strategy with a simple LSTM model can help improve the elastic property prediction on sparse well data. We demonstrate the robustness and effectiveness in terms of visual inspection and relative accuracy measure of the proposed method by using the SEG SEAM Interpretation Challenge dataset Phase I and comparing our results with Mustafa et al.'s (2021) work.
Karst Mapping on Carbonate Build up Using Advanced Spectral Decomposition and Enhanced Variance Filter Technology at Offshore Malaysia
Authors: Othman Haziqah Othman , Zhao Hongwen Zhao , Mohsin Norshida Mohsin , Singh Rajput Seemant , Isa Salbiah Isa , Awang Bujang Awang Amirul Zakry Awang Bujang , Ishak M Anwar Ishak , Azmi Afifah Azmi , Wong Wong Chan , Mishra Santosh Mishra , Rosselly M Noor Afifi Rosselly 
Published: October 2022

Abstract
Karstification is one of the major culprits for drilling issues (e.g., mud loss/blowout/wellbore collapse) in carbonate fields. Hence, it is crucial to precisely identify and predicate paleokarst distribution before formalizing a drilling plan. In this study, an isolated Miocene carbonate buildup in the offshore of Malaysia which is covered by a 3D marine seismic survey is selected for Karst mapping. Geological study shows that the carbonate buildup is bounded by two boundary faults and carbonate bodies were altered by multiple episodes of faulting and subaerial exposure related karstification. Extensive karstification is also evident by total mud losses in wells penetrating carbonate succession. Two in-house technologies: Advanced high-resolution Spectral Decomposition (ASD) and Hessian Filter-enhanced Variance (HFV) were used to illustrate the discontinuities within carbonate bodies and map Karst distribution. Well calibration with ASD and HFV results demonstrates that 1) Carbonate buildup can be clearly distinguished from surrounding clastics by specific (bright orange-colored) boundaries against dull colored clastics in RGB blending images; 2) Karst-related cavernous systems can be depicted by dendritic pattern variation in ASD images and HFV anomalies; 3) Linear discontinuities caused by fractures/faults are also highlighted by the results of ASD and HFV. It can be concluded that the combination of discontinuities revealed by ASD and HFV and with appropriate well and core calibration is a reliable way to predicate karstified reservoirs within the offshore carbonate buildup.
Acid Stimulation Campaign in Ghana Offshore Using Riserless Light Well Intervention Vessel
Authors: Leo Giuseppe , Borra Simone , Pasquali Paolo Giovanni , Sala Gianluigi , Borri Luca , Flamminio Davide , Stocchi Donatella , Mastrocola Carlo , Lazzari Andrea , Tadini Matteo , Ferraro Lorenzo , Fiameni Antonio 
Published: October 2022

Abstract
Scope of this paper is to describe the acid stimulation campaigns carried out in Ghana Offshore field between 2019 and 2020. The campaigns were carried out with a Light Well Intervention (LWI) vessel using different subsea equipment which allowed to safely perform the stimulation operation connecting the vessel to the X-tree production facility.
Reducing Laverda Canyon Field Production Uncertainty with Early Lifecycle Time-Lapse 4D Seismic Data
Authors: Fairburn Maddison , Pedler Hayley Sophia , Louis Jai 
Published: October 2022

Abstract
A time-lapse seismic survey (4D) acquired over Laverda Canyon Field has provided significant value and reduced production uncertainty early in the field lifecycle. At time of monitor one (M1) acquisition completion in April 2020 approximately 9% of the expected ultimate recoverable volumes were produced over the initial nine months of production. Horizontal wells targeting the two high-quality, vertically adjacent, oil and gas bearing reservoirs produce via waterflood. Prior to start-up, compartmentalisation was identified as a key risk due to interpreted high stratigraphic and structural complexity however, initial production data indicated greater connectivity than predicted.
The 4D successfully shows changes resulting from production within the field. Inversion of the final data to compressibility using a wave-equation-based amplitude-versus-offset approach assisted with interpretation by reducing noise and providing a direct property to correlate the impact of changing saturation and pressure within the reservoir. Water sweep, gas evolution, gas movement and pressure increase responses were calibrated at the wells prior to extrapolating interpretation of fluid flow away from well control. These insights were used to guide updates to the reservoir model. An updated fault-framework provides additional structural connectivity via cross-juxtaposition of reservoirs. Polygons corresponding to vertical stratigraphic connectivity via erosive down-cutting channels provides additional stratigraphic connectivity. Dynamic reservoir modelling has utilised connectivity polygons as well as more traditional history-matching parameters to show an overall improvement in replicating field production. Additionally, the reservoir model has been used to simulate the observed 4D response.
Improved understanding of field behaviour unlocked with the 4D has resulted in a higher level of confidence in the model for reservoir management and forecasting. Optimisations to the field operating strategy include revisions to the waterflood strategy to improve sweep and reduce gas migration and improved flexibility in voidage management. Future strategic facility decisions regarding project end of field life, development and assessment of near field tie-in opportunities will benefit.
Innovative Technique Using High Resolution Resistivity Image in Estimating Coal Seam Gas Reservoir Permeability
Authors: Oraby Mahmoud , Luft Joao , Zhou Fengde , Kuznetsov Dan , Keogh Sean , Alboub Mohamed 
Published: October 2022

Abstract
Permeability is one of the important reservoir properties for oil and gas reservoirs. It directly impacts the reservoir's ability to produce and is considered a key factor to delineate reservoir sweet spots for optimum well placement and successful development strategies. However, the permeability prediction is difficult for coal seam gas (CSG) reservoirs due to the presence of complex geological conditions which cause the lateral and vertical heterogeneity on the coal seam. The objective of this study is to present a practical petrophysical approach where the estimation of coal permeability is possible under the mapping of fractures and cleats using high-resolution microresistivity image logging data. This technique provides meaningful results that can integrate better with known coal geological criteria such as ranking and lithotypes. Furthermore, it helps better analyze production data and enhance history matching calibration.
Post-processing technique using resistivity inversion model and mud filtrate resistivity allowed to calculate fractures and cleats aperture as well as porosity. Fracture and cleat properties, i.e. density, length, area, aperture and porosity, were inputs for permeability calculation using fracture permeability published equations. Also, a multilinear regression (MLR) model was built for permeability estimation by utilizing the burial depth and properties of fractures and cleats.
The coal seam obtained modelled permeability is a continuous curve capturing vertical heterogeneity in both qualitative and quantitative ways. The MLR model improved the match compared to the published permeability equations. Results show that the modelled MLR permeability perfectly matches the actual diagnostic fracture-injection/falloff test (DFIT) and wireline formation tester mini-DST permeabilities. The study showed the role of petrophysical logging in evaluating coal permeability by minimizing the uncertainty associated with the traditional permeability estimation. The technique provides denser permeability points for the static model, significantly enhancing the model properties distribution. It is important to mention the benefit of this technique in selecting the best reservoir portion of the target seam during lateral wells planning.
Study on the Labyrinth Screw Pump for Heavy Oil Production
Authors: Wang Zhuoyu , Zhu Jianjun , Cao Guangqiang , Zhu Hongwu , Zhong Ruizhi , Zhu Haiwen 
Published: October 2022

Abstract
As widely used in onshore and offshore oil production, the electrical submersible pumps (ESPs) suffer from significant performance degradation for producing high-viscosity hydrocarbon fluids. In this paper, a new design of the labyrinth screw pump (LSP) is proposed to facilitate the high-viscosity oil production, which may partially replace the application scenarios of ESPs for heavy oil extraction. Based on the cellular supercharging theory proposed by Golubiev, a prototype of LSP was designed and manufactured, while an experimental facility was built up to test pump's performance at different rotational speeds and viscosity fluids. A fitting function was used to summarize the influence of different operating conditions on the H-Q curves by regression analysis. The applicability of the affinity law to LSPs was verified, which is widely used in centrifugal pump performance analysis. The internal flow characteristics was investigated by computational fluid dynamics (CFD) simulations. With the obtained results, the dimensionless flow and head coefficients of LSPs were able to be correlated by a non-linear relationship. Compared to ESPs, LSPs were found to be more suitable for conveying highly viscous fluids.
Method of Characteristics Based Model for a Coaxial Borehole Heat Exchanger
Authors: Duggal Rohit , Rayudu Ramesh , Hinkley Jim , Burnell John , McGuinness Mark 
Published: October 2022

Abstract
Mature petroleum fields provide readily accessible wells for geothermal energy extraction in many parts of the world. Likewise, the major hydrocarbon-producing region of New Zealand, the Taranaki region, has many mature wells with high temperatures (∼150 °C) measured at the bottom. Borehole heat exchangers could be a cost-effective way of producing geothermal energy from these wells. Therefore, the purpose of this study is to present a mathematical model capable of evaluating the potential of geothermal energy production from unused wells.
We first set up our mathematical model using the Method of Characteristics for the wellbore heat exchangers. A co-axial borehole heat exchanger is selected for our study due to its simple design and popularity in use. The model is then validated against the analytical results available in the literature.
For the first time, a study utilizing borehole heat exchangers to produce geothermal energy is being conducted in New Zealand. This study will help boost interest in reusing unused wells for residential and industrial direct use applications. Based on our model, the capability of alternate fluids such as supercritical CO2 to further enhance the performance of heat exchange will be analyzed in the future.
Evaluation of the Potential of Foam Producing Microorganism Improving Heterogeneity of Permeability for Novel Microbial Foam EOR
Authors: Ito Miu , Sugai Yuichi 
Published: October 2022

Abstract
The foam improves heterogeneity of permeability in oil reservoir and contributes to enhancing oil recovery. Both surfactant and gas are alternatingly injected into oil reservoir in foam EOR, therefore, it has several challenges: high cost of surfactant, formation of precipitation with bivalent cations, adsorption of surfactant on reservoir rock, etc. This study proposes the microbial foam EOR which overcomes those challenges by having microorganism generate foam in-situ. We have found an ability of a microorganism belonging to Pseudomonas aeruginosa to generate foam under anaerobic conditions. This study investigated the source materials constructing the foam and capacity of the foam to improve the heterogeneity of the permeability.
The challenges of our study are the reproducibility of the foam generation and the foam stability. This study therefore examined the source materials of the foam to understand the mechanisms of the foam generation. We focused on protein, which has been suggested as a possible component of the foam in our previous studies, and examined the relationship between the amount of foam generated by P. aeruginosa and the concentration of protein in its culture solution. As a result, a positive correlation was found between them. This result indicates that the foam generated by P. aeruginosa is composed of the protein produced by the microorganism.
Next, the performance of the foam decreasing permeability of high permeability porous media was evaluated through sand pack flooding experiment. P. aeruginosa was injected into a sand pack and cultivated in-situ. The post-flush water was injected into the sand pack after three days’ in-situ cultivation to measure the permeability. As a result, the permeability of the sand pack was successfully decreased to half after the cultivation. The permeability of a sand pack in which P. aeruginosa was injected with culture medium and in-situ cultivated was successfully decreased to half of initial. The efflux of bacterial cells of P. aeruginosa was detected after injecting 1.3 pore volumes of postflush water, which shows that the postflush water flowed through areas other than the area where P. aeruginosa grew and produced the foam. These results indicate that the foam produced in-situ by P. aeruginosa is effective for improving the heterogeneity of permeability in oil reservoir.
This EOR can be operated at low cost without expensive chemicals. Because the foam produced by P. aeruginosa is induced by proteins, the precipitation will not be formed in oil reservoir. The stability of protein-induced foam is higher than that of surfactant-induced foam in the presence of oil or high saline conditions. The microbial foam EOR therefore has high potential improving the heterogeneity of permeability in oil reservoir more effectively than the conventional foam EOR.
Digital Transformation of Offshore Structure Weight Control Management into Digitally Integrated and Intelligent Analytical Tool
Authors: Alias Nur Dalila , Wong Bak Shiiun , Anas Wan Zalikha , Sulaiman Nur Amalina , Epui Mildred Vanessa , A Rahman Azam , A Rahman Ahmad Rizal , Yeoh Sue Jane , Abdollahzadeh Asaad , Ngadan Linda William , Tang Horng Eng , Chooi Wai Fun , Khan Riaz , Ng Sook Moi , Saminal Siti Nurshamsinazzatulbalqish , Ibrahim M Mujiduddin , Hamid Marklin , Suhaili Ave Suhendra , M Hisham M Said Farhan 
Published: October 2022

Abstract
Leveraged on the abundant weight data comprised of more than 200 offshore platforms, a smart digitalized analytical tool called i-WEIGHT, an integrated weight control tool consisting of three (3) main modules: centralized multi-discipline weight database module for all offshore platforms, seamlessly linked with Insights dashboard module in providing actionable insights, and weight predictive module supported by Machine Learning (ML) model was developed. This paper discussed the Minimum Viable Product (MVP) Phase 1 development outcome, using a close-loop weight control ecosystem for continuous update of validated weight data in Module 1, and eventually improve & enhance capability of both the EDA and Predictive module. Using a supervised machine learning algorithms, the identified target variables were observed to provide weight prediction between 16% to 38% of Mean Absolute Percentage Error (MAPE), using Extreme Gradient Boosting Regressor (XGBR) algorithm. Top 10 important features were identified for each target variable, which provide insights to the operators on critical data required for topside with identified missing equipment weight data for future i-WEIGHT improvement. Based on more than 200 integrated platform topside data gathered for this study, consolidated insights from the data enabled operators to identify the threat of current data quality and thus bringing forward a promising opportunity to enhance platform weight data management system. Having a centralized and automated platform weights data, this tool has the potential answers for United Nations’ Sustainability Development Goals, in particular Goal 9.4, where the study represents a small but crucial step to upgrade from an existing conventional process into a digitally driven operation, introducing a sustainable ecosystem in offshore structure weight management, thus fostering sustainable growth within the industry.
Berri Increment Novel Waste Heat Recovery System
Authors: Alotaibi Fahad M , Al-Dossari Faisel M , Al-Majed Fahad M , Al-Hajri Ali M , Al-Zahrani Talal A 
Published: October 2022

Abstract
Berri Crude Increment Project (currently in the Execution phase) will install a new oil processing facility. As part of the project, a new thermal hot oil system will be provided to heat the crude oil for the desalting and stabilization process to meet the product specifications. This heating is primarily achieved through three hot oil heaters (furnaces) fueled by natural gas in a closed heating circulation system. The objective is to maximize the energy utilization and efficiency of the oil processing facility by integrating the waste heat of the plant turbines’ exhaust with the plant process heating network.
The project added in the scope a waste heat recovery system as part of the hot oil loop to recover the energy and maximize the plant’s efficiency. The waste heat recovery consists of heat exchangers mounted on the plant combustion gas turbines to recover the exhaust heat and supply it to the plant heat demand. These turbines are fueled by natural gas to drive the water injection pumps at the facility.
This design enhancement will minimize fuel gas burning in the hot oil heaters to supply the required process heating, and will reduce combustion product emissions from the hot oil heaters’ stacks to atmosphere. The anticipated benefits are as follows:Recover energy of up to 75 MW that represent 50% of the total heating duty.Optimize lifecycle cost through Savings by reducing fuel gas burning by 50%.Reduce greenhouse gases emissions by minimizing the hot oil heaters’ fuel gas consumption.Improve equipment and plant efficiency (10% turndown of process heating can be achieved).Minimize single point of failure through the increase of plant availability with flexible process heating design.
This energy integrated design is one of a kind among conventional oil and gas surface facilities with very high energy recovery capability. The facility is expected to recover 50% of its total thermal duty needed by processes through efficient energy utilization. In addition, substantial environmental advantages are foreseen by reducing the plant combustion effluents. This is important for a processing facility located in an area that is considered a hub of several marine and environmental initiatives of Saudi Aramco.
Pigging the Unpiggable: A Case Study of Waxy Crude Oil Pigging Simulation and Field Implementation
Authors: Anuar Astriyana , A Rasib Amira , M Norpiah Rohaizad , Ali Zalina 
Published: October 2022

Abstract
This paper presents the various challenges faced by a 10-km waxy crude oil pipeline at Field 23, as the pipeline has not been able to be pigged for almost one year due to recurring pigging issues such as broken/damaged pigs, vibrations and high pressures that were close to trip settings. The implemented pigging frequency as per operating philosophy is every two weeks. However, the frequency has been extended based on field experience. Due to these issues, Operation team immediate action is to devise a pigging program that works and to avoid recurring issues. Flow Assurance (FA) engineers working together with Operation team devised a plan that incorporates lab analysis and conducted desktop studies which include field data analysis and application of various FA simulation tools. The main challenge is to develop a robust FA model that is reliable enough to use for detailed analysis, be able to reproduce field data and use it to develop the most suitable pigging program. Additionally, it is worth noting that the pipeline has gone through rigorous wax chemical optimization that potentially contribute towards wax incremental issues in the pipeline. It was also observed that the fluid has changed tremendously from initial design basis due to fluid blending from non-associated gas (NAG) and oil zone and production header temperature mixing effects. Therefore, the initial operating envelope was found to be no longer suitable for this pipeline. From extensive lab analysis, fluid modelling update, metocean data calibration and wax deposition tuning, the FA models were able to match the field conditions within &lt; 10 % variance. A field tuned baseline model was developed. Several options have been proposed and analyzed such as varying pig types, pigging and chemical methods where extensive FA modeling were performed to evaluate the suitability of each method/application to develop a more suitable pigging program. A detailed workflow on the chosen program was then produced based on a progressive pigging method utilizing multiple pig types at a reduced flowrate with chemical application. Although wax dissolution effects from wax dissolver chemical was not modeled, this model-based approach was a success in that we were able to reduce pig stuck risk during actual field implementation. The success of the waxy crude oil pipeline pigging campaign has sparked an immediate interest among the Production/Operation engineers especially on the application of a robust FA models, in which when it is well calibrated, enable effective and immediate troubleshooting of issues at site. This work has set a benchmark for FA engineers to update/develop a well-calibrated FA model during operation phase to facilitate optimization and troubleshooting programs.