bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gold Hydrogen - New Opportunities from Surface Processing Perspective
Authors: Sahak Muhammad Zakwan Mohd , Daud Nik Mohd Radi Nik Mohd , Thant Maung Maung Myo , Jones Ernest A 
Published: February 2024

Abstract
The term "Gold hydrogen" or "white hydrogen" typically refers to hydrogen naturally found in subsurface reservoirs. The discovery and recovery of this natural hydrogen is still limited at large scale, however it is emerging as a potential hydrogen source to be explored, as the world moves towards Energy Transition and hydrogen as clean energy fuel source of the future. To effectively produce and export hydrogen from the reservoir, new surface facility design considerations and changes need to be adopted and implemented that are different from a typical natural gas production process. Production of natural hydrogen provides several advantages compared to industrial methods of hydrogen production which are associated with high energy cost for water electrolysis and CO2 emissions from steam methane reforming process. However, literature sources indicate that hydrogen content in the produced gas from the subsurface ranges from 0-100%, and usually is accompanied with presence of other gases such as CO2 (up to 3.7%), nitrogen (up to 99%), hydrocarbon gases (up to 50%), helium (up to 8%) and argon (up to 0.5%). Due to the difference in compositional range among all gases, different processing schemes are required. The key challenge faced is the purification of hydrogen from other gases especially in the presence of helium which is closer to the molecular size of hydrogen making typical separation technology such as Pressure Swing Adsorption (PSA) ineffective. Due to the commercial potential of helium, it is also worthwhile to separate helium for sales, with one potential technology identified is metal hydride separation. This proposed concept of hydrogen recovery (consisting of bulk separation, purification and hydrogen-helium separation) is planned to be deployed at a pilot-scale natural hydrogen production facility at an onshore site.
Rapid Depressurization and Corrosion Evaluation of OCTG Connections for CCS Injection Wells
Authors: Mauger Pierre , Martin Pierre , Boufflers Laurent , Rodriguez Diana 
Published: February 2024

Abstract
Carbon capture and storage (CCS) is a key technology to decarbonize many industrial processes. Premium OCTG connections are key components in CCS wells ensuring structural and tightness performance between the casing and the tubing pipes. Vallourec research and development departments continue to develop a comprehensive connection test protocol for CCS injection wells and investigate impact of low temperature and the corrosion performance of premium OCTG connections with liquid CO2.
CO2 phase change can occur in the tubing during the process of injection or during the shut-in of the subsurface safety valve generating the Joule-Thomson effect due to rapid depressurization. The temperature can plummet to '60°C in regular operations and could lead to the failure of the tubing in the well posing risks to human safety and the environment due to uncontrolled CO2 release. A rapid depressurization test has been put in place to reproduce this phenomenon.
The aim of this paper is to describe the tests performed under combined load of tension and external pressure with liquid CO2. The specimens tested in rapid depressurization were in super duplex stainless steel. They were inspected after these tests to check if corrosion or pitting were present inside the connection.
A premium OCTG connection in 5-1/2″ 20.00# 25Cr 80ksi with dope free solution and compatibility configuration has been tested according to the CCS test rapid depressurization evaluation. The first test was performed at 80% of pipe capacity with 100 bar of liquid CO2 with an ambient temperature at 25°C. The specimens experienced a temperature of '60°C in 7 minutes without any leak or structural failure. A second test was carried out under pure external pressure at 473 bar and a third test with combined loads: tension at 510 kN and external pressure at 473 bar. The liquid CO2 pressure was at 100 bar and 20°C as initial temperature condition. During the rapid depressurization the temperature went down from 20°C to '60°C in 10 minutes without any leak or structural failure. A failure test was also conducted under depressurization above 100% of connection capacity.
The connections with metal-to-metal seal tested in rapid depressurization were compared to configurations tested for their corrosion resistance in autoclave. All the configurations tested show no indication of pitting nor corrosion on the seal.
The size tested with rapid depressurization evaluation demonstrated this product is compatible for CCS injection wells in the most severe conditions. The additional physical data also allowed to better understand the temperature drop in full-scale tests. The metal-to-metal seal with dope free solution presented no corrosion after these tests and confirmed the suitability of premium OCTG connections to liquid CO2.
Research Analysis of Reforming Hydrogen Fuel for FLNG Application
Authors: Lin Chan WE , CK Tam Ivan , Kr Dev Arun 
Published: February 2024

Abstract
The LNG production platform is one of the main contributors of carbon emissions in the Marine and Offshore industry. It's called floating liquid natural gas (FLNG). This platform is most popular in the Oil and Gas offshore industry. Modern FLNG aims to improve overall LNG production efficiency. It uses high power machinery to meet the process plant's needs, which leads to high carbon emissions. The first step of the FLNG clean energy trial effort involves using clean energy for onboard power generation. To achieve a clean energy mindset, it is vital to use clean fuels like hydrogen. These fuels can replace hydrocarbon fuel usage for FLNG power generation. This research paper aims to use the reforming method to produce Hydrogen onboard from Natural Gas and boil-off gas (BOG). BOG is vaporised gas from the LNG tank. Mainly, Hydrogen fuel for FLNG power generation. Interestingly, methane can be obtained from natural gas and BOG onboard FLNG. Since gas management onboard is crucial, most of the excess BOG is burned without use as an energy source. One reason to choose Hydrogen is the energy carrier. It consists of atoms with a higher H/C ratio, containing more energy per mass.
Vitality of Natural Polymers in Safe Flooding in Offshore Operation: Road to Caspian Sea Implementation
Authors: Serikov G. , Hashim A. A. , Pourafshary P. , Zhuniskenov Y. , Mohyaldinn M. 
Published: February 2024

Abstract
Application of Enhanced oil recovery methods (EOR) in offshore oil fields are getting more popular with the advancement in technology and chemicals used. Polymer flooding is one of the most successful projects to improve water mobility by increasing the viscosity. Application of polymers promises to improve areal sweep efficiency and consequently recovery factor. However the main concern associated with injection of chemicals in offshore oil fields is the possibility of leakage and pollution of marine systems affecting biodiversity and environment.
The following study focuses on rheological properties of three bio-polymers: Xanthan gum, Wulan gum and Potato starch in laboratory conditions as viscosifying agents. The study involved characterization of each polymer at different concentrations from 500 ppm to 5,000 ppm dosage. Sensitivity analysis on various reservoir temperatures were also performed from 25°C to 55°C to fit Kazakhstan reservoirs along with sea water salinity to simulate Kazakhstan reservoir conditions. Results from rheological studies showed that 3,000 ppm is considered as the optimum concentration from Xanthan and Wulan gums, Potato starch did not show any good results as viscosifying agent. Further temperature effect studies showed that both Xanthan and Wulan gums have a strong temperature resistance and does not experience dramatic viscosity drop at reservoir temperatures in a range of 8-14% of loss. However, salinity effect showed that Wulan gum tends to lose rheological properties in high salinity environment and high viscosity drop. Rheological studies showed that Xanthan gum is highly resistant to salinity and temperature changes, while Wulan is only temperature resistant.
The obtained rheological data were correlated with the Ostwald–de Waele power-law model to characterize fluid flow parameters, shear thinning behavior and identify n, k values. The correlations affirmed the shear-thinning properties of Xanthan and Wulan gums, a critical attribute for effective oil displacement in offshore reservoirs
Core flooding experiments were performed for each polymer at the optimum concentration, salinity and temperature. Carbonate cores were used to simulate reservoir conditions and assess the effectiveness of natural polymers in improving oil recovery. Core flooding experiments with Xanthan and Wulan gums showed incremental oil recovery of 30 and 20% respectively. In the context of Kazakhstan's Caspian Sea, these findings herald a promising future for enhanced oil recovery, leveraging the robustness of natural polymers in challenging offshore conditions. Overall, these polymers demonstrated impressive results in displacing oil under harsh offshore reservoir conditions
Real-Time Eccentricity Correction of Through-Tubing Cement Log Data Using Machine Learning
Authors: Zeghlache Mohamed Larbi , Marroquin Ivan , Rourke Marvin , Yang Qinshan , Tarasov Alexander 
Published: February 2024

Abstract
One of the major challenges associated with downhole Through-Tubing Cement Evaluation (TTCE) is the varying tubing or first pipe eccentricity (ECC) inside the casing or second pipe. As ECC varies, the signal or response from the cement behind the casing will change, therefore making it critical to have a method to measure and correct or compensate for the ECC effects in order to obtain a reliable cement bond log. The research study presented in this paper covers a real-time ECC correction algorithm for cement log data using neural networks. The scope covers the design, implementation, and evaluation of the ECC algorithm, as well as some of the potential benefits for the novel through-tubing evaluation services.
The ECC algorithm uses a neural network that is trained for various logging environments. The neural network generates a weight matrix that is defined in a calibration file, which is then loaded into the acquisition software prior to the logging operation. The neural network structure consists of multiple layers of interconnected nodes, each with its own set of weights and activation functions. The algorithm works by reducing the effect of eccentricity on the bond index accuracy of through-tubing cement data. Inputs to the algorithm encompass both time and frequency domain signals from six azimuthal segments around the pipe to model the ECC effects. The neural network effectively demodulates the impact of tubing eccentricity and outputs ECC-corrected cement segment signals. The paper presents the overall approach and details of the process involved in designing, implementing, and evaluating the ECC algorithm during data acquisition and post-processing.
The simulation and lab test results from this study demonstrate the effectiveness of the ECC algorithm in reducing the effect of eccentricity on through-tubing cement data. The real-time application of the ECC algorithm results in more accurate bond index measurements, which can improve well integrity evaluation. This technique is particularly useful in situations where eccentricity is an important factor affecting bond index, where the tool string and tubing positions in the well leads to a higher uncertainty in interpreting cement evaluation data. Overall, the developed algorithm adds significant value to the improved hardware and software solutions as part of the research effort towards a comprehensive TTCE solution for rigless operations.
This paper presents a comprehensive description of the ECC correction algorithm's design, implementation, and evaluation, and demonstrates its effectiveness in improving bond index accuracy. The integration of machine learning tools to provide reliable real-time cement bond logging without the need to pull tubing, presents a major advance in well integrity evaluation that further improves safety, efficiency and cost.
Numerical Simulation of Enhanced Gas Recovery from Methane Hydrate using the Heat of CO2 Hydrate Formation
Authors: Ito K. , Sawano Y. , Tada K. , Sato T. 
Published: February 2024

Abstract
Methane hydrate exists abundantly under the seafloor of Japan's exclusive economic zone and has attracted attention as a domestic natural gas resource. Depressurisation is one of the methods for producing methane gas from methane hydrate under the seafloor, in which methane hydrate is dissociated into water by pumping up water and reducing the surrounding pressure. However, the production rate decreases after a certain period of time because the stratum is cooled by the endothermic dissociation of methane hydrate. To overcome this situation, an enhanced recovery method has been proposed: namely, CO2 is injected into the stratum to generate CO2 hydrate, and the surrounding area is heated by the exothermic formation of CO2 hydrate to promote the dissociation of methane hydrate. This combination of CO2 hydrate storage and enhanced recovery of methane hydrate is important because it can achieve both efficient methane gas production and the reduction of greenhouse gas emissions.
Experimental Investigation of the Impact of Low Salinity Water and Hydrochloric Acid Solutions as Halite Precipitation Reduction Agents for Enhancing CO2 Injectivity in Deep Saline Aquifers
Authors: Darkwah-Owusu Victor , Yusof Muhammad Aslam Md , Sokama-Neuyam Yen Adams , Tackie-Otoo Bennet Nii , Turkson Joshua Nsiah , Radzali Iswadi B. , Yusof Shahrul Rizzal B. M. , Fjelde Ingebret 
Published: February 2024

Abstract
Reducing CO2 emissions from the atmosphere is one of the most important contributors in the fight against climate change. Salt precipitation, a critical challenge in CO2 storage, adversely affects CO2 injectivity by reducing formation permeability and porosity, consequently diminishing CO2 storage efficiency. This research seeks to experimentally evaluate the effectiveness of Low Salinity Water (LSW) and Hydrochloric Acid (HCl) in mitigating salt precipitation during the injection of CO2 into saline reservoirs to enhance injectivity. In a two-phase experimental approach, this study first simulates salt precipitation scenarios with varying brine salinities (70g/L and 170g/L) to mimic formation damage during continuous CO2 injection. The second phase critically evaluates the impact and effectiveness of LSW and HCl as treatment fluids, as compared to freshwater. The core flooding experiments were conducted at 60 °C and 1600 psi. The initial and final permeability and porosity of the core samples were measured to ascertain the extent of improvement or impairment pre-and post-flooding using brine. The findings reveal a reduction in both porosity (11% - 30%) and permeability (28% to 75%) due to salt precipitation. LSW treatment proved to be the least effective, likely due to clay swelling. Conversely, HCl treatment exhibited high dissolution potential, achieving a 67% improvement compared to initial permeability for formations with low initial brine concentrations. Interestingly, higher brine salinity during HCl treatment resulted in an increased concentration of free ions, facilitating a rapid reaction between Cl- ions and Cu2+ and Fe3+ ions of the resulting solution. These reactions led to the formation of FeCl3 and CuCl2 salts causing a green coloration in the effluent. This observation suggests the possibility of tertiary reactions that could lead to other in-situ geochemical reactions and mineral precipitation.
First Application of Innovative Dual-String Barrier Evaluation Tool for Annular Cement Validation in UAE
Authors: Singh K. , Biyanni H. , Serry A. , Almaazmi A. , Benberber M. Rebbou , Tamuli A. , De Barros A. J. , Khalil T. , Abdalla A. , Bose S. , Wielemaker E. , Ishberdina G. , Yaacoub M. , Shaposhnikov P. 
Published: February 2024

Abstract
Evaluation of the annular barrier is an integral part of well construction, integrity, and reentry scope. The current industry practice is to run sonic and ultrasonic tools to evaluate the barrier quality across a single string. However, many wells require the evaluation of the barrier behind a second string, for which today, the inner string must be pulled out to log the outer string. The dual-string technology allows the simultaneous evaluation of both string annuli without having to remove the inner string.
An innovative technology using a combination of multimodality ultrasonic imaging and multimode advanced array sonic measurements has been developed to evaluate the barrier quality in the second string annulus. With consideration of the underlying measurement physics, this work explored the implications of well geometry, the impact of pipe-to-pipe standoff, the correction, and the validation scheme. A verification method for the actual pipe-to-pipe standoff versus estimated standoff provides an accurate approach for the evaluation of cement slurry placement and practices. Formation compressional and shear measurements were also enabled via dual-string logging simultaneously.
The dual-string barrier evaluation technology was deployed in an offshore well in Abu Dhabi. Data were initially recorded in a 13 3/8-in. single string using sonic and ultrasonic tools; afterward, data were recorded with both 9 5/8-in. and 13 3/8-in. dual-string configurations. Data interpretation and benchmarking provided insights on the qualitative barrier state and demonstrated dual-string measurement robustness and accuracy. Further insights were drawn in the evaluation of formation acoustic properties using compressional and shear measurements acquired across two strings and its use for other subsurface geoscience applications.
Dual-string barrier evaluation technology demonstrated the potential CAPEX saving in heavy-casing design by providing insights to the first- and second-string annuli simultaneously. Additionally, this technology provides a new solution to assess zonal isolation for the surface casing. This is particularly important as the quality of cement behind this surface casing is usually not evaluated, which creates a gap in proving the required zonal isolation information. Without the information about the top of cement, the isolation between the Simsima formation (the flowing formation) and the aquifer is not proved.
Overcoming Realtime Formation Evaluation Data Transmission Challenges While Drilling with Microbubble and Hollow Glass Sphere Mud System
Authors: Bagga Pawandeep , Khatri Shubhada 
Published: February 2024

Abstract
The paper describes the challenges faced in Formation evaluation Data transmission while drilling through Mud Pulse Telemetry during first deployment of Hollow Glass Sphere (HGS) and Microbubble Mud Systems in Western Offshore India. The oil and gas operator faces considerable difficulties when drilling and evaluating formations in directional within these low-pressure and depleted reservoirs. HGS and Microbubble Mud Systems was utilized for reducing drilling fluid density for prevention and mitigation of losses, while drilling through a producing reservoir section with low pore pressures.
To tackle the issue of significant or complete loss of drilling fluid during drilling in the low-pressure reservoir, a low-density micro-bubble drilling mud system was implemented with a density ranging from 6.3 to 7.5 pounds per gallon (ppg). However, the presence of micro-bubbles in the drilling mud led to easy compression, substantial distortion, and attenuation of the mud pulse telemetry signal. Consequently, the real-time logging-while-drilling (LWD) log suffered from a lack of data density, rendering it less valuable to the client. A detailed Study was done considering the pump efficiency, flowrate, mud pulse telemetry principles, pulser design etc. and a new technique was developed in order to deliver high density formation evaluation LWD Data.
Identifying the limiting factors and implementing risk mitigation strategies were crucial steps taken to minimize the loss of real-time data and ensure a continuous and uninterrupted logging-while-drilling (LWD) data stream for operator to make Realtime Decisions. Pulser Servicing, Pulser Design change along with software enhancements helped to deliver Mud pulse Transmission up to 20 BPS. The modified configurations of the mud-pulse telemetry module proved to be of great value in providing an uninterrupted logging-while-drilling (LWD) log with an adequate density of data, meeting the requirements of the operator's sub-surface team.
The paper ends with conclusion of best practices which can be incorporated to deliver quality data. This pulser and telemetry system can be clubbed with any LWD Services including NMR, Formation Pressures and Electrical Imaging while Drilling.
Application of Machine Learning in Predicting Cement Properties
Authors: Shamsan Abdulmalek , Jimenez Walmy Cuello , Jandhyala Siva Rama Krishna 
Published: February 2024

Abstract
Cementing operations consists of placing cement slurries between casing-casing and casing-formation to achieve multiple objectives including zonal isolation, corrosion resistance, isolation of water bearing formations, etc. Cement slurries are tailored in the laboratory environment simulating downhole conditions to achieve the required placement times (i.e. thickening time) for the slurry to remain in a liquid state during pumping. This study presents an artificial intelligence model developed to predict the cement slurries thickening time based on historical experimental data, along with the ability of the model to continue learning based on the flow of output results.
Collected data sets of different input parameters were gathered and studied to estimate cement thickening time. Based on statistical analysis, only five inputs (Pressure (psi), measured depth (ft),bottom hole circulating temperature (°F), retarder additive concentration (%), and slurry density (ppg)) had a positive impact on the correlation coefficients between the inputs and target properties. A model was developed using Python programming language to predict the thickening time. The data was fed into the model to train and test the input factors impacting the target property using a neural network method.
The model expressed an integrated relationship between the training and validation data which resulted in an optimum learning performance revealed by a loss function plot. As a result, the scatter plot for prediction vs actual has illustrated the prediction of the thickening time with an average accuracy of 83% confirmed by the model box plot. The model validation consisted of employing a set of data to predict the thickening time for more than 11 slurries with an average absolute error of 6%.
Model implementation indicated that over 200 hours per month were saved due to reduced number of thickening time test iterations required to be run before executing the job which positively impacting operational efficiencies associated with cost, resource allocation, and investigation assessment. The outcome results from this model and the process used herein could be scaled up to consider other properties, i.e. ultra-sonic cement analyzer UCA, fluid loss, free fluid, etc.