bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Optimization of Overall Layout for Ultra-Deepwater Subsea Dynamic Umbilicals
Authors: Zhu Hong , Yang Jin , Xue Rui , Xu Dongsheng , Zhao Yuhang , Zhang Xun , Dai Shenghui , Zhan Shibo , Yan Xinye , Li Gengchen 
Published: February 2024

Abstract
This paper addresses the growing global demand for energy, specifically focusing on the ultra-deepwater regions of the South China Sea, a rich source of oil and gas. In this context, the study of ultra-deepwater umbilical cable systems, a critical component in offshore oil and gas field development, becomes increasingly significant. The paper analyzes the composition, design challenges, and performance under extreme conditions of ultra-deepwater umbilical cable systems. Utilizing recent data collected from umbilical cable systems that are tied-back to six floating platforms in the South China Sea and dynamic analysis data from the OrcaFlex software, the study employs an enhanced Backpropagation (BP) neural network and Bayesian Optimization method for multi-objective iterative optimization under specific target functions, achieving an optimal overall design for the ultra-deepwater dynamic umbilical cables in the region.
The results indicate that the predictive accuracy and generalization ability of the BP neural network model are significantly enhanced through the method combining the Bayesian Optimization algorithm with the improved BP neural network. The refined BP neural network achieves a mean squared error (MSE) of 0.011 and an R2 score of 0.98, demonstrating high predictive accuracy and generalization capability. This optimization reduces the BP neural network's training time by over 60%, meeting the precision requirements for umbilical cable design optimization. After more than 5000 iterations using the improved BP neural network combined with the Bayesian Optimization algorithm, the study identifies an optimal set of design parameters for umbilical cables that are tied-back to floating platforms in the South China Sea. This optimization reduces the maximum effective tension and overall axial tension in the umbilical cable system by over 15%, decreases cable curvature by more than 25%, and lessens the impact of vortex-induced vibrations by over 30%. Furthermore, the BP neural network-based optimization method employed in this study is successfully applied to the design of umbilical cables for floating platforms in the South China Sea, providing scientific and technical support for the design and optimization of ultra-deepwater umbilical cables. This research has significant implications for the exploitation and utilization of China's deepwater marine resources.
Optimizing Underwater Inspection for Freespan Threat via Predictive Analytic Approach
Authors: Karim Khairol Hazman A , Juzilman Raizil Aisyaizni , Abdullah Nur Asiah Maryam , Hambali Siti Hawa , Ahmad M Nazri , Ali Napiah M Nazmi M 
Published: February 2024

In the dynamic landscape of pipeline management, PrAnSpan emerges as a game-changing predictive analytics tool, redefining how we approach freespan inspection scheduling by intelligently forecasting freespan behaviour and conditions, prolong inspection intervals thus optimizing resource allocation, minimizing disruptions and reducing GHG due to vessel movement.
Predictive Analytics for Freespan, or ‘PrAnSpan,’ introduces a novel approach in handling dynamic freespan in pipelines. The methodology involves leveraging machine learning techniques and integrating both asset-specific and historical data made available by offshore pipeline operators. The primary objective of conducting PrAnSpan is to enhance the efficiency in managing pipeline freespan by optimizing the cost associated with underwater inspections and facilitating more informed decision-making especially for costly immediate span rectification.
The implementation of this approach includes the development of a web-based predictive analytic algorithm and a corresponding dashboard. These tools are designed to predict the formation and behaviors of freespan along the pipeline for specific years by combining machine learning capabilities and historical data which aims to provide a proactive and cost-effective strategy for addressing and managing pipeline freespan issues. The predictive analytics algorithm becomes a valuable tool for anticipating freespan concerns, ultimately contributing to more efficient and informed decision-making processes in the realm of pipeline maintenance and inspection.
Reusing Existing Oil and Gas Wells for CO2 Storage with Machine Learning Algorithm
Authors: Islam Raka , Sohel Rayhana , Redzuan Farah Rosmaniza , Hasan Faruque 
Published: February 2024

Abstract
This paper aims to guide decision-makers, particularly in the United States, through the transformation of oil and gas wells into geologic carbon storage sites, with a focus on regulatory nuances. The primary objective of this study is to facilitate informed decision-making for a sustainable energy landscape. The paper presents a simple decision tree algorithm with a dataset consisting of few injection wells from Denver unit of the Wasson Field, West Texas. Data was collected from publicly available sources and the step=by-step approach of collecting data from Texas Railroad commission sources is also provided. The decision tree algorithm assess class II wells’ eligibility for class VI permits. Class II wells are injection wells, typically used for EOR. Class VI permits are for injecting carbon dioxide into deep rock formations for long term storage (geologic sequestration). These permits are governed by the U.S. Environmental Protection Agency (EPA) under the Underground Injection Control (UIC) program. EPA has outlined some rules for transforming class II wells into class VI wells. The decision tree algorithm categorizes wells for class VI permits into distinct classes: those suitable for conversion with minor modifications, those requiring additional information, those needing significant modifications, and those deemed unsuitable for this purpose. This approach provides a user-friendly and simplified initial step for decision-making, particularly beneficial for operators without a background in machine learning. The transformation of existing oil and gas wells into geologic carbon storage sites, as outlined in this paper, not only aligns with environmental sustainability goals but also presents a financially advantageous prospect for operators. Repurposing these wells for geologic sequestration of carbon dioxide offers a dual benefit—contributing to the global effort in mitigating climate change while potentially qualifying operators for the 45Q tax credit in the United States. The 45Q tax credit serves as a powerful economic incentive, providing operators with financial rewards for successfully implementing CCS technologies, thereby fostering a more sustainable and economically viable energy landscape.
Pre-Installed Cable Protectors Can Reduce RIH Time for Completions
Authors: Bibby J 
Published: February 2024

Abstract
This paper will demonstrate the rig time savings and the associated cost reductions available by using pre-installed cable protectors during run-in-hole operations for completions when downhole cables and control lines are being deployed. Pre-installed cable protectors can also greatly reduce the number of personnel operating in the ‘red zone’ thereby improving safety.
Analyzing and Controlling Factors Impacting Offshore Condensate Optimization with Digital Tools
Authors: Kongkiatpaiboon Suradech , Prangsawan Kanchana , Trithepapirak Sakka , Soponpalarom Apipol , Charungrattanapong Worasak 
Published: February 2024

Abstract
Condensate production is an essential aspect for typical offshore field development and facility optimization. This work intends to analyze the primary impact factors that relate with condensate optimization and how they are controlled using digital technology, resulting in more effective hydrocarbon monetization, reliable operation, and better outcomes. The project focuses on heat exchanger design and optimization, Reid vapor pressure (RVP) prediction and optimization, middle chain hydrocarbon allocation, and digital tools for operation and troubleshooting.
Process simulation runs have been completed and the results are compared with anticipated operating windows. The investigation reveals some areas of improvement: 1) heat exchangers design improvement to help with frequent fouling, 2) more reliable data model to supplement RVP online analyzer data, 3) better optimization of intermediate chain hydrocarbon (C4 – C5), and 4) the implementation of real time optimization tools. Several alternatives were investigated in depth for each difficulty, and digital tools are developed to overcome these problems. These include data science model deployment, heat exchanger performance monitoring, and real-time optimization dashboards.
It is anticipated that the solution provides offshore operation with monetary benefits and ease of operation when utilizing the tool. These include 1) heat exchanger redesign from parallel to series operation to reduce fouling effects, 2) fancy tube installation on tube bundle to improve its efficiency, 3) dashboard to track heat exchanger performance, monitor it in real-time, and forecast the next cleaning cycle, 4) data science model evaluation and deployment for the RVP model, 5) an alert mechanism if the model's accuracy is unacceptable and requires retraining, 6) a dashboard to monitor the allocation of middle-chain hydrocarbons, and 7) a central dashboard covering all key impacts to advise operation engineers on how to best capture the hydrocarbon values with condensate production. After implementation, numerous benefits are observed. These include increased operational efficiency, enhanced RVP prediction and control, reduced burden from manual investigation, and increased condensate yield as a result of optimization efforts.
Condensate optimization issues have a long history in offshore operations, but the affecting factors are generally unknown or have not been thoroughly investigated. This study demonstrates the effectiveness of digital tools for troubleshooting and optimization. The expanding demand for empowered digital tools, as well as the offshore operation team's positive experience with the technology, demonstrate the practicality, value, and potential of modern digital tools for continuous monitoring of platform assets and processes.
Sanding Onset and Volumetric Sand Production in Gas Hydrate-Bearing Sediment
Authors: Wang Yarlong 
Published: February 2024

Abstract
Sanding onset and sand production under non-isothermal conditions are of interest both for thermally related Enhanced Oil Recovery (EOR) in conventional reservoirs and fluid production in gas hydrate bearing formations (GHBF) for sand control and optimized production purposes. The thermal-hydraulic-mechanical coupling with hydrate decomposition (THMD) process must be considered once a supercritical condition is surpassed during wellbore depressurization, heating and a combined process during drilling, injection and production. In this paper, the mechanical responses considering the THMD effect is calculated by a poro-elastplastic model in which a linear Mohr-Coulomb yielding criterion is incorporated. The formation cohesion is assumed to be hydrate saturation-dependent. Sand production onset and the volumetric sand production is determined by an effective plastic strain (EPS) and postulated proportional to the sanding radius, respectively. The sand rates both from conventional and GHBS of experimental testing data are simulated and validated by the proposed model.
Coupled Geochemistry CCS Modelling: How Much Simplification is Required?
Authors: MousaviMirkalaei Seyed Mousa , Edmondson Mark Douglas 
Published: February 2024

Abstract
Carbon sequestration is the process of capturing and storage of atmospheric carbon dioxide. The objective of any carbon sequestration project is to store CO2 safely for hundreds or thousands of years with a goal of mitigating global climate change. Based on literature, coupled geochemistry with fluid flow is essential for modelling of CCS mechanisms such as multiphase flow, solute transport, mineral dissolution, and precipitation. Geochemical modelling has an important role in understanding these processes, in the short term there will be some dissolution due to CO2 injection to the reservoir and in the long-term, mineralization of CO2 could potentially occur. This mineralization may then subsequently have a large effect on the storage volume and storage development plan.
In numerical dynamic modelling there are always simplifications made to reduce the simulation runtime, however, for coupled geochemistry, oversimplification may cause incorrect results. The question which this paper is going to answer is how much simplification is required in the coupled geochemistry dynamic flow modelling of CCS.
To answer the question, a sector model from an aquifer with one CO2 injection well is extracted and coupled geochemistry with compositional simulation modelling is performed. The model included CO2 solubility and geochemistry with three minerals (‘Anorthite’, ‘Calcite’ and ‘Kaolinite’) and their respective geochemical reactions. Then the same model is simplified by decreasing the number of minerals and reactions to only ‘Calcite’ and one reaction. In the model with three minerals ‘Anorthite’ is dissolved whereas ‘Kaolinite’ is precipitated throughout the simulation and ‘Calcite’ initially is dissolved and then precipitated. In the model with one mineral there is a very small amount of ‘Calcite’ dissolution. The results showed that the amount of mineralization in the model with three reactions is about 10% of the injected CO2 after 1,000 years from the start of injection while in the simplified one-mineral model is almost zero.
The results of this study prove that oversimplifying the geochemistry potentially can cause the model to miss some of the active geochemistry processes, leading to erroneous results in the simulation. The simplification should be based on the lab mineralogy data (the amount of each mineral in the core) and the static ageing experiments. However, it is proposed at least 3-5 minerals to be considered in the model even though the small amount of each mineral could have a large secondary affect on the reactions from another mineral.
Hydrogen and Natural Gas Blending in Gas Network – A Case Study of Kalgoorlie-Kambalda-Esperance Gas Pipelines in Western Australia
Authors: Sofian Mohammed , Haq Bashirul , Alshehri Dhafer , Mizanur Rahman Mohammed , Zaman Ehsan 
Published: February 2024

Abstract
Hydrogen (H2) blending in natural gas (NG) pipelines is one of the pragmatic solutions to reduce the carbon footprint from natural gas usage. This work evaluates the potential of H2-NG blending in the Kalgoorlie-Kambalda-Esperance (KKE) – a part of the Western Australia (WA) transmission network. This work reports the effect of varying gas compositions such as H2, H2O, CO2, and CH4 on corrosion, erosion, and pressure profiles in the KKE.
The Kalgoorlie-Kambalda-Esperance pipeline is owned by APA Group and Esperance Pipeline Company in WA, and it is a 394-kilometre transmission pipeline that extends from Kalgoorlie to Esperance in WA. A simulation model of the KKE was developed using PIPESIM-Net software and a GIS map to replicate the steady-state flow of gaseous streams accurately. Appropriate boundary conditions were applied at the network's nodes, including the source and sinks, to ensure the model's reliability. All necessary input data for the model were taken from the APA website, published reports, and literature. Initially, the model was validated using historical data from the APA group. Then, sensitivity analysis was conducted with varying concentrations of H2and CH4, CO2, and H2O to evaluate the impact of gradually increasing hydrogen concentration within the flowing stream on the network's overall performance.
This analysis provides valuable insights into the impact of hydrogen concentration on the system, offering a comprehensive assessment of potential risks and opportunities of H2-NG blending in transmission networks. The developed model highlights distinct pressure profile fluctuations as the H2 fraction increases from 0% to 100%. Notably, a consistent pressure increase is observed within the 0-20% H2 concentration range. Furthermore, the study indicates a slight reduction in corrosion rate, even at maximum allowable concentrations of corrosive components such as water and carbon dioxide. On the other hand, the erosional velocity ratio (EVR) exhibits a negligible increase with rising H2%. Both corrosion rate and EVR remain well within industry-accepted limits, further affirming the overall viability and safety of the system.
The main novelty of this work is that no similar report is available in the literature where the KKE is simulated to explore the pressure, corrosion, and erosion effects of H2-NG blending.
Success of Directional Casing Drilling (DCD) Technology Delivering East Asia's Deepest and Longest High Inclination Angle 13-3/8in Casing Section, Alongside Four Other Wells Batch Drilled in Field BC
Authors: Baharudin Alif Shamir , Soong Alfred , Najmi Nik Fahusnaza Nik Mohd , Ravendrnathan Khabilashini , Chai Beng Seow 
Published: February 2024

Abstract
Due to persistent clay swelling issues leading to borehole breakouts in Field BC, the operator opted to seek alternative solutions to mitigate risks of wellbore stability (WBS) issues. Conventional drilling with drill pipe and running casing separately exposes the open hole for a long time, in between (Bottom Hole Assembly) BHA tripping out to casing running. This in turn results in significant water absorption by shallow clay dominant formations leading to cavings and collapse. To resolve this issue, Directional Casing Drilling (DCD) technology was explored in order to drill and case the hole at the same time. DCD technology is an enabler for batch top hole section drilling optimization of Field BC in Malaysia to drill and secure every foot drilled to section target depth (TD) in a single run and through the restricted wellhead design.
With extensive studies to mitigate the risk and challenge, the DCD technology was successfully implemented in Field BC for five wells. Moreover, several others added benefit of DCD technology such as reduced personnel head count during the operation on the rig floor and improved rig safety throughout the operation by eliminating the manual pipe, minimal chemical consumption during DCD technology with seawater and hi-vis instead of Pump and Dump (PAD) mud or Synthetic Oil Based Mud (SOBM) helps reduce the impact on the sea habitat. Most importantly, with these benefits introduced by 13-3/8″ DCD technology, this drilling campaign has saved the operator 3 days with carbon emission reduction of 126 ton.
Unexpected Rapid Corrosion in Mooring Chains Explained
Authors: Bennet D. G. , Roffey P. 
Published: February 2024

Abstract
High rates of corrosion had led to severe material loss in a low-alloy medium carbon steel Tether Chain from an offshore mooring system after only 5 years in service. The material losses were caused by extensive corrosion pitting and wear damage from adjacent links. Substantial levels of biomass were detected in the seabed soil and seawater at depths below 20 meters. The corrosion products on the chain link surfaces also tested positive for slime forming microorganisms indicating mature biofilm formation with inclusion of microenvironments which enabled proliferation of diverse aerobic, facultative and anaerobic heterotrophic populations. Those identified by molecular microbiological methods employed included Acid-Producing, Iron-Oxidising, Sulphate-Reducing and Sulphur-Reducing populations. The findings from the analysis confirmed a mechanism of Microbiologically Induced Corrosion (MIC), with wear rates further exacerbated by the action of rubbing wear continually exposing fresh steel surfaces which corroded in the bacteria rich environment. The repetitive, cyclical nature of the combination of rubbing and corrosion resulted in unexpected, accelerated corrosion rates.
Performance-Based vs Prescriptive-Based Abandonment Approach; A Review
Authors: Darmawan G. R. , Prasetya A. E. , Susilo S. D. 
Published: February 2024

Abstract
70% of Indonesia's old oil and gas wells will have no economic value and have to be abandoned as ruled by the government as it comes to the end of the well life cycle. It's part of decommissioning an entire field with environmental preservation called Abandonment and Site Restoration (ASR). There are two kinds of approaches to abandonment, prescriptive-based and performance-based. Each country has its regulations but refers to one of those two approaches. Indonesia's permanent abandonment standard is prescriptive-based, this was compared and evaluated to international permanent abandonment standards for abandonment design, and the philosophy behind it.
Literature studies are performed to understand the abandonment philosophy for Performance-Based versus Prescriptive-Based to give proper suggestions or improvements. Based on the literature study, contrast gap analysis and suggestions provided to ensure a proper permanent abandonment approach to avoid any future leaks or re-abandonment operation as part of well integrity assurance after abandonment
This paper will define and evaluate the gap analysis between typical prescriptive-based abandonment standards, like Standar Nasional Indonesia 6910-2022, Section 19.2, Abandonment of Wells; ISO-16530-1, Chapter 10, Well Abandonment Phase; OGUK, 2015a, and NORSOK D-010, Rev. 4, Chapter 9 with a performance-based approach.
The gap analysis has shown significant abandonment improvement opportunities, especially in terms of materials that can be used for plugging/isolations, reservoir isolations barriers, annular barriers, also abandonment philosophy and practice.