bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unlocking the Potential of Mud Logs and LWD in the Gulf of Thailand Using Machine Learning
Authors: Palviriyachote S. , Misra S. , Moelyono S. , Ekkawong P. , Tonburinthip T. 
Published: November 2024

Abstract
The gas field in the Gulf of Thailand stands as one of the largest natural gas reserves in Thailand, with over 30 years of development history and more than 1,000 penetrated wells. With the power of machine learning and availability of historical data, there are opportunities to revolutionize traditional processes. Use of machine learning for log synthesis can help reduce expenses and operational risks associated with traditional well logging methods, including service fees, rig time, and potential retrieval challenges. This study aims to utilize machine learning techniques to predict well logs by analyzing Mud Log and Logging While Drilling (LWD) data.
The proposed machine learning workflow utilizes raw mud log data (gas show content) and LWD measurements (gamma-ray and resistivity) to predict essential well logs—bulk density (RHOB), neutron porosity (NPHI), and compressional sonic travel time (DTC). This study employs various machine learning techniques, including Random Forest Regressor, Gradient Boosting Regressor Neural Networks and Support Vector Regression (SVR). The data sources come from the wells in the Gulf of Thailand, ranging from depths of 1,000 to 2,800 meters TVDSS. With a resolution of 0.1 meter, the training dataset will consist of 10,000 to 28,000 points for each well. These wells exhibit porosity levels between 13% to 30% and permeability below 100mD. The formations mainly composed of channel and point bar sands within a fluvio-deltaic system. Challenges arise from variations in reservoir properties across different depositional facies, clay content, and fluid presence, affecting prediction accuracy between original training data and predicted wells.
The model effectively predicts well logs utilizing gamma-ray, resistivity, gas content data, and applies feature creation through polynomial transformation as input. Among the models tested, the Random Forest Regressor and Gradient Boost Regressor models prove to be the most accurate predictor. The random forest model achieves prediction accuracies with Mean Absolute Percentage Errors (MAPE) for bulk density (RHOB), neutron porosity (NPHI), and compressional sonic travel time (DTC) of 0.965%, 9.27%, and 2.536%, respectively.
Such a predictive model is suitable for existing wells with only LWD and Mud Log data, lacking open-hole logs due to operational issues encountered during drilling. The cost savings from reducing well log fees and rig time in one of the fields could amount to $1 million USD per month. Beyond log synthesis, the methodology opens avenues for identifying reservoir and fluid types, enhancing decision-making in oil and gas exploration and production activities in the Gulf of Thailand.
Comparative Study of Nitrogen, Carbon Dioxide, and Hydrogen Pore Occupancy, Connectivity and Ostwald Ripening in Carbonate Rocks
Authors: ALZaabi A. , Alzahrani H. , Alhosani A. , Bijeljic B. , Blunt M. J. 
Published: November 2024

Abstract
High-resolution three-dimensional micro-CT imaging is used to investigate nitrogen, carbon dioxide, and hydrogen injection in reservoir carbonate rocks. The images were analysed to ascertain gas saturation, pore occupancy, ganglia size and connectivity across the sample. The experiment studies a water-wet reservoir carbonate rock that is filled with synthetic brine before and between each gas injection. The experimental conditions involve unsteady-state gas injection at a pressure of 9 MPa, a temperature of 60°C, gas injection at a rate of 0.005 mL/min, and brine injection at a rate of 0.1 mL/min to remove all the gas in the sample. The sample is firstly saturated with brine, followed by N2 injection, and then brine injection. Images are taken throughout each injection phase and after waiting 24 hours after gas injection. This procedure is replicated for the CO2 and H2 cycles. The saturation of gases in the sample after injection were as follows: N2 around 25%, CO2 approximately 21%, and H2 around 18%. While the N2 saturation slightly decreased after 24 hours, the CO2 and H2 saturation remained relatively stable over time. The saturation profile reveals that N2 and H2 experience more significant changes during the waiting period caused by Ostwald ripening compared to CO2 as the gases propagate to the centre of the sample. Capillary pressure measurements based on interfacial curvature at around 80% brine saturation indicate a significant decline for N2, from 1.46 kPa to 1.18 kPa after 24 hours. CO2 experiences a decrease in pressure from 1.17 kPa to 1.05 kPa over 24 hours, while H2 shows a minimal decline in capillary pressure with time remaining at approximately 1.04 kPa. Pore occupancy and ganglia analysis indicate N2 occupying pores mostly above 25 µm radius, and the saturation increase in the larger pores after 24 hours. Throat radii larger than 18 µm show an increase in N2 saturation, indicating improved connectivity, as supported by the normalized Euler number. CO2 predominantly occupies pores from 30 to 40 µm with minimal change. H2 occupies pores larger than 19 µm with minimal changes with time and throats larger than 8 µm with increased saturation with time that suggests enhanced connectivity. Overall, this study provides a useful reference for comparing N2 and CO2 displacement and trapping behaviour after waterflooding which have been studied extensively, with those for H2, and is applicable to gas storage projects within carbonate reservoirs.
Automated Refractory Dry-Out Operation
Authors: Sengupta Subhendu , Goveas Vincent , Al Seyabi Mathla , Karunakaran Raghesh 
Published: November 2024

Abstract
This paper is based on successful implementation of automated heater refractory dry out operation in Habshan-5 SRU using Yokogawa's Exapilot software, in continuation of past success of digitalisation of critical batch operation like SRU start-up & shut down, Ethane recovery /rejection change over in NGL unit. Objective was to automate SRU heater refractory dry out operation (with or without refractory repair) as per standard operating procedures to ensure process safety & asset integrity by minimizing human error. Besides it aims to reduce dry out time & thus energy required for dry out operation.
Scope is to integrate Habshan-5 SRU heaters like reaction furnace, Incinerator heater dry out automation with existing SRU start up automated modules.

Procedure
Heater refractory dry-out is critical operation in SRU startup & carried out manually prior to automation.

Drawback
Maintaining temperature profile as per OEM dry out curve poses challenges in manual operation.
Custom solution based on Exapilot & past dry out data used for automating SRU heaters refractory dry-out.
Two modules for each heater were built. Viz.
Each module consists of

Prediction block
Which predict air, fuel demand for every target temperature based on past & current data

Monitoring block
This block scans all critical parameter related to dry-out & alert operator if deviation

Adaptive control
This sub module adjusts dynamically the controlling parameter like Air/Fuel based on feedback to maintain target temperature within its range. Conceptually it learns from past action & improve to follow the temperature profile.
Validated modules were deployed in Expilot Server and seamlessly integrated with rest of SRU start up modules which enabled operator easy access to perform dry-out operations during start up in an efficient manner exactly as specified in the OEM given dry out procedures. Post testing on U552 heaters dry out & subsequent data analysis & operation feedback revealed the following benefit.

Business Benefits
This data driven & prediction enabled, heater refractory dry-out automation, first of its kind in ADNOC highlights the success stories of Habshan-5 & Sulphur digital transformation journey of critical batch operations.
Development of Searching Strategy for Micro-Leakage in Natural Gas Stations Based on TDLAS Methane Detectors with PTZ Controller
Authors: Xiao Fei 
Published: November 2024

Abstracts
Detecting and locating micro-leakages pose significant safety challenges in the gas and petroleum industries. Typically, a single Tunable Diode Laser Absorption Spectroscopy (TDLAS) methane detector equipped with a PTZ controller can effectively mitigate the risks associated with potential leaks at natural gas stations. However, the lack of a dedicated search and localization function often results in operators spending considerable time pinpointing the source of a gas leak. To address this issue, a series of experiments and simulations were conducted to investigate integral concentration and evaluate its characteristics and influences. This led to the development of three search algorithms, which were assessed in a virtual environment: Global Searching Based on Steady Concentration (GSSC), Global Searching Based on Real-Time Concentration (GSRC), Spherical Search Based on Real-Time Concentration (SSRC). These algorithms were tested under field conditions, focusing on accuracy and response time across various scenarios. The results indicate that integral concentration, affected by factors such as optical path and concentration distribution, exhibits distinct characteristics. Notably, the highest values for both integral and gas concentrations consistently occur at the leak source. In the simulated leak scenarios, all three proposed algorithms successfully identified the leak locations. Among them, the SSRC algorithm demonstrated superior efficiency and accuracy by accounting for real-time concentration dynamics and the evolution of gas cloud diffusion. In field tests conducted at natural gas stations, the SSRC strategy effectively located leak sources with rates exceeding 300 ml/min and integral concentrations above 3000 ppm·m, achieving this within a 15-minute time frame.
A Comparative Study of High-Modulus Polyethylene (HMPE) and Steel Wire Ropes for Offshore Subsea Lifting and Installation
Authors: Schlömlich Stefan , Vinther Morten Loell , Eijssen Marc , Kanters Marc 
Published: November 2024

Offshore lifting and deployment operations are integral components in the lifecycle of subsea infrastructure, encompassing activities from initial construction to maintenance and eventual decommissioning. The choice of lifting and deployment accessories, such as lifting slings and deployment lines, significantly influences the safety, reliability, efficiency, and cost-effectiveness of these operations. Traditionally, steel wire ropes have been the industry standard due to their robustness and reliability. However, recent advancements in synthetic materials have introduced material such as high-modulus polyethylene (HMPE) ropes, specifically those made with Dyneema® fibers, as a compelling alternative.
This paper presents a comparative analysis between HMPE and steel wire ropes, focusing on how advanced material modelling can capture important response mechanisms, and demonstrating this with practical applications in the offshore field of use. The study aims to guide the selection of materials in various operational scenarios by evaluating key performance factors.
ELMA (Export Loading Monitoring & Analysis): Transformative Innovations in Custody Transfer Monitoring and Analysis at PETRONAS Export Terminals
Authors: Daud Nurul Shaidatul Shima Mohamad , Shahrun Datu Darul Anwar Datu , Fauzi Nur Melatee Mohd 
Published: November 2024

Abstract
The ELMA (Export Loading Monitoring & Analysis) system represents a significant advancement in custody transfer operations at PETRONAS Export Terminals. By integrating automation, machine learning, and real-time data processing, ELMA addresses key challenges in maintaining accurate and reliable custody transfer measurements. The system enhances the reliability of these measurements by automating key monitoring tasks, reducing reliance on secondary measurement methods, and providing operators with analysis trends and actionable insights. This paper discusses the development, deployment, and impact of ELMA, focusing on its four key modules: Meter Factor Control Chart, Meter Factor Prediction, Loading Performance, and Prover and Tank Status. The implementation of ELMA has led to improved measurement accuracy, reduced reliance on secondary measurement methods, and enhanced early detection of critical issues. The early results highlight ELMA's effectiveness in optimizing custody transfer operations, positioning PETRONAS as a benchmark for innovation in the oil and gas industry. Despite its success, challenges related to data quality, system integration, and ongoing maintenance remain areas for future improvement.
Empowering Petrophysics: Elevating Thin-Bed Analysis with Integrated Advanced Logging and Digital Workflows
Authors: Tolioe W. A. , Cavalleri C. , Lerdsuwankij T. , Hakimi S. , Yusuf N. A. , How L. , Zakaria M. H. B. , Kassim M. S. A. 
Published: November 2024

Abstract
In response to domestic and international energy demands, oil and gas companies are positioned to discover new reserves by making investments in exploration activities. The oil and gas discovery must meet economic criteria and be feasible for development. Low- resistivity pay reservoirs remain a topic of interest because the characterization of these reservoirs containing laminated shaly sand hydrocarbons and thin-bed layers have traditionally been challenging. The standard resistivity techniques often underestimate hydrocarbon assessments due to presence of conductive laminated shale, resulting in the field or block to fall into marginal or sub commercial categories.
Understanding reservoir properties is essential to estimating the hydrocarbons in place because assessing net pay and hydrocarbons saturation presents challenges in reservoirs characterized by high-shale content. This paper presents a novel approach for integrating logging measurements, including nuclear magnetic resonance (NMR), 3D resistivity, and borehole imaging, with advanced laminated sand analysis (LSA) to refine reservoir characteristics and determine accurate formation properties. The LSA method incorporates 3D resistivity and NMR data, employing probabilistic methods to calculate true reservoir properties of sand fraction and resistivity, and quantify laminated shale content. LSA results undergo standard petrophysical interpretation using deterministic approaches, ensuring consistency across the analysis. Formation evaluation employing probabilistic techniques further refines mineral volumes and corrected porosity, essential inputs for interpreting integrated well logs. NMR-factor analysis across the entire interval, with T2 cutoff values distinguishing clay and free fluid, enables computation of clay-silt-sand volume and effective porosity to help calibrate the petrophysical model.
Advanced techniques, including 3D resistivity anisotropy, dip-corrected outputs, NMR poro-facies, and factor analysis contribute to precise reservoir property determination. Digital workflows enable rapid data processing and analysis, providing valuable insights within time constraints.
This comprehensive approach significantly enhances reservoir understanding, producing improved hydrocarbon estimation. The results indicate substantial increases in net pay and hydrocarbon pore volume, highlighting the effectiveness of this innovative thin-bed analysis approach to maximizing hydrocarbon recovery potential in challenging shaly sand environments.
Structured Energy Trending and Performance Assessment for Combustion Engine (SETPACE©) - An Innovative Approach to Decarbonize Combustion Emissions from Upstream Operations
Authors: Ali Z. , Azuhan A. , Lee Y. , Hakim M. Abdul , Taib N. 
Published: November 2024

Abstract
This paper introduces a state-of-the-art tool known as SETPACE© (Structured Energy Trending and Performance Assessment for Combustion Engine) which has the capability to validate authenticity of fuel gas flow meter reading, improving fuel gas accounting; quantify fuel efficiency (thermal efficiency) degradation by comparing theoretical vs actual fuel consumption for individual machines based on current operating parameters; quantify fuel gas reduction from various improvement opportunities and generate near-to-real fuel gas forecast. PETRONAS Upstream Energy Efficiency (EE) journey, which began in 2021, aims to reduce energy consumption without affecting production, thereby increasing gas sales and decreasing Greenhouse Gas (GHG) emissions. By 2023, SETPACE© had been widely implemented across all domestic assets in Malaysia. More than 90% of fuel gas (energy) within these assets is consumed for gas compression and power generation. The assessment of over 170 turbomachines across more than 80 oil and gas facilities has revealed that approximately 18% fuel gas reduction from year 2023 conventional forecast is discovered through accounting and forecasting improvement. Baseline results show gas turbines’ fuel efficiency estimate ranging from 4% to 32%. Fuel inefficiency in machinery typically stems from two (2) main factors: performance degradation and low operating loads. Machines with significant deviations in fuel efficiency often consume more fuel than necessary due to deteriorated performance. Addressing this through performance restoration, typically as part of routine planned maintenance, can reduce fuel gas consumption. This approach is particularly viable if the cost is offset by fuel gas savings, with an estimated maximum reduction of 11% from the actual fuel gas reported in 2023. Gas Turbine Generators (GTGs), designed for redundancy and to manage upstream uncertainties, may operate at low loads, leading to inefficient fuel use. While this operational philosophy ensures reliability, it results in higher fuel consumption. Optimizing GTG train operations is estimated to achieve an additional 5% reduction in fuel gas consumption. Furthermore, energy demand optimization and partial electrification is estimated to contribute an additional 11% reduction in fuel gas usage. Decarbonizing combustion through Energy Efficiency (EE) measures is anticipated to reduce GHG emissions by approximately 0.8 to 1.4 million tons of CO2 equivalent per year and recover energy, resulting in an estimated annual savings of USD 20 to 35 million.
Influx-Free Barrier for Oman Salt High-Pressure Water Zones
Authors: Khan Anum Yousuf , Salazar Jose , Bogaerts Martijn , Peng Fei , Ashraf Shameed , Jain Bipin 
Published: November 2024

Abstract
A unique case of salt cementing occurs in the subsalt wells in the south of Oman, which contains pressurized water-bearing zones across salt beds. To achieve zonal isolation, the cement must overcome the influx of water during the cement hydration period, create strong bonding with the salt formation to prevent the flow of formation fluids following placement, and be able to address the stresses of salt creep to avoid loss of isolation.
A three-step approach was developed to address each of the challenges during the cementing of a 7-in. liner. First, a detailed salt cementing study was performed to determine the sensitivity of the slurry design to contamination from the salt formation. Second, using a stress simulation, a fit-for-purpose flexible and expandable slurry design was proposed to overcome wellbore stresses. Third, a novel laboratory testing procedure was developed to confirm the shear bonding of the cement slurry to the halite salt formation.
In the event that the 8.5-in. openhole section across the salt formation encounters high-pressure water zones, mud weight can be increased to 18.5 lbm/gal to prevent influx. Therefore, a high-density cement slurry is required to maintain overbalance during the cementation of the 7-in. liner. The effect of contamination was determined in the laboratory by comparing various concentrations of formation salt and the optimal design using potassium chloride (KCl) in the base fluid.
Using the outcome of proprietary stress simulations, the slurry was optimized to have a low Young's modulus and expanding properties to prevent any failure of the cement sheath integrity and migration of formation fluids resulting from a micro annulus.
To confirm bonding between the slurry and the salt formation, salt cores were used in the laboratory to confirm shear bonding between the slurry and the formation.
The final slurry design was optimized in the laboratory to the specific job conditions in terms of cement transition time and setting time. Cement placement and displacement procedures were adjusted to avoid large pressure changes in the wellbore that could potentially result in the debonding of the cement from the casing.
A fit-for-purpose high-density, flexible cement slurry was developed to overcome the challenges encountered while drilling the salt formation. The slurry has been used on seven 7-in. liner jobs since 2023. Since the implementation of the new slurry design, all of the wells have achieved zonal isolation across the salt sections and have isolated the high-pressure water zones, enabling the operator to drill the low-pressure reservoir interval below the salt formation without the need for remediation, saving time and lowering costs.