bluuebunny/crossref_metadata_2025 huggingface dataset:
Research Analysis of Reforming Hydrogen Fuel for FLNG Application
Authors: Lin Chan WE , CK Tam Ivan , Kr Dev Arun
Published: February 2024

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

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

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

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

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

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

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

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.
Optimization of Perforation Phasing for Improving Uniformity of Perforation Erosion Through Computational Fluid Dynamic Modelling and Downhole Video Imaging
Authors: Yuan L. , Hu S. L. , Mu L. Y. , Wang D. L. , Yang X. T.
Published: February 2024

The limited-entry technology was a key technology in the multistage fracturing of shale oil and gas horizontal wells to help distribute fracture fluid among multiple perforation clusters evenly. However, perforations could be eroded and enlarged because of high-speed and continuous abrasion by the proppants, resulting in unequal inflow and uneven cracks propagation between perforation clusters, which caused low efficiency of the fracture treatment. Considering that the perforation erosion has not been fully understood yet, special attention should be paid to this aspect of research.

In this paper, perforation erosion models were built using computational fluid dynamics (CFD) to simulate the distribution of the flow field when high-speed fracturing fluid with proppants injected perforations. Then, the flow field analysis was conducted to investigate the impact of the perforation phase on erosion and chambering. Finally, pre-fracturing and post-fracturing erosion data were obtained by the downhole video imaging technology, which was employed to validate against simulation results. Based on above technics, the erosional pattern of perforation would be clearly revealed.

The CFD simulation results demonstrated that, perforations were rapidly eroded to droplets (a typical streamline shape) from the initial round shape because of the much higher erosion rate on the upside of the perforation (near toe) than the downside (near heel). The CFD modelling also noted that there was huge difference of erosion rate between perforations at different phases. Perforations at phase 0 degree (high side of the horizontal wellbore) suffered the minimum erosion rate while perforations at phase 180 degree (down side of the horizontal wellbore) got the maximum. As for perforations at phase 90 and 270 degree, their erosion rates were intermediate，and the values were similar. What's more, the above simulation results were verified by the downhole video imaging data. Most post-fracturing perforations look like droplets. The most eroded perforation was near phase 180 degree with an average diameter of 18 mm which was 1.7 times larger than that of perforations near phase 0 degree (11 mm), while post-fracturing perforations at phase 90 and 270 degree were 13.5mm. Therefore, the 180 degree perforation phasing would help to reduce the uneven erosion and to avoid oversized perforations.

It was a novel approach to integrate the CFD modelling and downhole video imaging technology to quantitatively characterize the perforation erosion pattern, which presented a better dynamic understanding of perforation erosion rather than the previous static analysis by field observations or simulations. This approach would help the optimization of perforation designs and the improvement of field fracturing effect.
Managing Australia's Decommissioning Future and Building Regional Capacity
Authors: Norman F. G.
Published: February 2024

This paper provides an overview of the status of the Australian decommissioning industry and discusses actions and activities that are underway to ensure the industry is as prepared as possible for the growing volume of work it will face this decade. The paper also considers how the growing decommissioning workload can be managed across the region to deliver best in class outcomes and predictable outcomes for all involved.

Driven by reservoirs reaching the end of their production life, the age of existing infrastructure and changes to legislation, the volume of decommissioning activity occurring and planned in Australia has increased significantly this decade. This increase in activity has highlighted several gaps in the readiness across industry; operators have been largely focused on new developments and production with decommissioning taking a lower priority, service sector companies have delayed preparing for decommissioning work due to ongoing uncertainty of workload, and regulators had not been exposed to large enough volumes of decommissioning applications for their personnel to be prepared.

Since its establishment in 2020, the Centre of Decommissioning Australia (CODA) has been working to bring a greater focus on the opportunities and challenges facing industry as decommissioning becomes more common place. This has included CODA's initial work highlighting and quantifying the anticipated volumes and timeline of decommissioning works in Australia. Alongside producing the 2020 forward lookahead, CODA has also been developing reports, resources and tools to help Australian industry prepare for the US$40.5 billion of forecast decommissioning activity.

Regionally, decommissioning workloads are also growing. There is an increasing global demand for skills and equipment, and a growing intersection and tension between offshore decommissioning and offshore wind. Pressures are building on the supply chain to service demand for decommissioning services in Australia, in the Asia Pacific region and globally. Now is the time to explore deeper regional cooperation on this critical final phase of the oil and gas production cycle.
Machine Learning Cement Quality Risk Assessment
Authors: Salehabadi M. , Mohamad Yakup M. A. , Chung S. J. , Buang A. , Jaafar I. , Thanoon D. , Patel C.
Published: February 2024

One of the key elements of well abandonment process is the restoration of regional cap rocks, typically achieved by understanding of quality of cement behind casing by means of interpretation of cement bond logs. The main challenges of cement evaluation, however, are the availability of these logs where these are required, the cost of the acquisition of the data, and well accessibility issues which sometimes prevent the acquisition of the data. The intent of the project is to use machine learning technology to provide an assessment of cement quality based on learning datasets as inputs. Presented here is Phase 1 of a longer study as a proof of concept. Relevant data in the form of petrophysical data, geomechanics data and cement job reports were collated, and then machine learning techniques were applied to identify key parameters which may impact prediction of quality of cement, and subsequently algorithms can then be generated.
A Deep-Learning Framework for the Optimization of CO2 Plume Geothermal Power Production - A Pathway to Carbon Net-Zero
Authors: Katterbauer Klemens , Abdulaziz Qasim , Al Shehri Abdallah , Ali Yousef
Published: February 2024

Several businesses have recently developed CO2 plume geothermal technology (CPG). The concept proposes generating geothermal energy using CO2 trapped in salty aquifers. Compared to traditional geothermal concepts, CPG is unique. In this instance, the feedstock makes use of CO2 as a carrier fluid to draw heat from the subterranean reservoir. Furthermore, the system may use a typical sedimentary substrate rather than only shallow natural hydrothermal areas. Finally, CPG may continue to produce energy in low-temperature settings where it is currently not feasible to do so using traditional geothermal methods. For the purpose of maximizing power generation from a CPG system, we introduce a novel deep-learning optimization methodology. The framework employs a modified N-BEATS methodology. The method is built on an interconnected stack of backcast and forecast connections and ensembled feedforward networks. The framework's versatility with regard to numerous input parameters and different forecastable time series is one of its benefits. This is especially crucial for CPG to effectively capture changes in the temporal dynamics and temperature responses across the numerous CO2 injection and production wells. We assessed the framework on a simulated CO2 storage reservoir based in the Taranaki basin in New Zealand. Given the existence of a sizable saline aquifer that may be ideally suited for CO2 storage and CPG energy generation, the Taranaki basin has been extensively explored for CO2 storage. As input to the Neural basis expansion analysis for time series (N-BEATS) framework, we modeled 3.5 years of CO2 generation and injection for geothermal energy production. The network demonstrated high training performance, and the model's effectiveness was assessed based on the ensuing two years' worth of energy output. The global optimization framework is then combined with the deep learning framework to maximize energy production while modifying CO2 injection. A novel approach to improving energy generation from CO2 storage reservoirs, the new deep learning N-BEATS optimization framework for CPG power generation offers a sustainable means to reduce carbon footprint while delivering electricity.
A Novel Approach of Machine Learning Incorporating Physical Knowledge of Hook Load for Early Stuck Detection
Authors: Inoue Tomoya , Nakagawa Yujin , Kaneko Tatsuya , Wada Ryota , Abe Shungo , Yasutake Gota
Published: February 2024

Early detection of stuck pipe events is pivotal due to their role as major causes of non-productive time. Although researchers have adopted data-driven approaches, such as machine learning, challenging issues persist, such as limited datasets, limited stuck pipe events, and various causes of stuck pipe. This study proposes a novel machine learning approach that incorporates physical knowledge, explaining universal facts, to overcome the aforementioned challenges.

This study creates a prediction model that focuses on the hook load to predict occurrences of stuck pipes. To create the model, we adopted a novel idea that incorporates physical knowledge such as torque and drag models. Because the measured hook load contains uncertainties and is affected by operating conditions, the hook load is expressed using physical knowledge with unknown parameters, and the parameters are determined using data science technologies, including machine learning, based on adjacent historical hook load data. The prediction model is created using only the data in the normal conditions, and the model can express the hook load in normal condition. When the measured hook load exceeds that predicted via the model, it can be assumed that a larger a friction (drag) force is exerted, resulting in a high stuck risk. The deviation, calculated from the predicted and measured hook loads, is acquired, and finally, if the deviation exceeds the normal range determined through data science techniques, including machine learning, the risk of blockage is outputted.

This study initially introduces the stuck pipe predictions using both supervised and unsupervised machine learning approaches. Subsequently, we present machine learning integrating physical knowledge and demonstrate early stuck pipe detection using field data containing stuck pipe events. This novel machine learning approach incorporating physical insights may contribute to significant reduction of nonproductive time in drilling operations, potentially preventing well abandonment.
The Study of Supercritical Carbon Dioxide Trapping Behaviour in Carbonate Reservoirs Through Pore-Scale Imaging Analysis
Authors: Foo Y. Y. , Kashim M. Z. , Mazeli A. H. , Tewari R. D. , Menke H. P. , Singh K.
Published: February 2024

Severe climate change has urged the energy industry to revolutionalise the conventional technologies at pace to curb greenhouse gasses emission for more sustainable future. Carbon Dioxide (CO2) storage at subsurface geological formation remains as the most effective technique to store massive quantity of CO2 safely and permanently. Nonetheless, the flow and trapping behaviours of CO2 at supercritical condition within geological formation are very complex, particularly for the carbonate rocks attributed to the wide spectrum of rock fabrics, pore geometries and structures. This study aims to investigate the pore interconnectivity and residual CO2 trapping during the drainage and imbibition processes within porous media through digital rock technology. Native cores from three carbonate fields with different rock characteristics were plugged to obtain representative samples for the pore-scale coreflooding experiments. Brine and supercritical CO2 were injected into core plugs at temperature up to 120 °C and pressure up to 3000 psi. X-ray images of the saturated core plugs were obtained through micro computed tomography (Micro-CT) facilities after injection of 10 pore volume (PV) of CO2 and 5 PV of brine. Porosity, pore interconnectivity, fluid occupancy, saturation profiles and CO2 ganglia size distribution were measured and studied through the pore-scale imaging analysis. The results indicate that the saturation of CO2 after drainage and imbibition are strongly dependent on the local rock heterogeneity, specifically the presence and distribution of micropores within the rocks. All samples evidently show that micropores play critical role in pore interconnectivity. CO2 ganglia in one sample was observed to be well connected initially but fragmented into smaller sizes after brine imbibition and, lastly, there was no CO2 percolation within the pore network if the flow rate was too low. This paper presents a detailed study in investigating the flow and trapping behaviour of CO2 at supercritical state, providing new insights to the important factors which influence the CO2 trapping. Deeper understanding of the flow and trapping mechanisms is essential to formulate an effective CO2 storage development plan, ensuring minimum injectivity and containment risk throughout the storage period.
Drillpipe Conveyed Casing and Cement Evaluation Allows for Acquisition of Critical Measurements in Parallel with Existing Well Operations
Authors: Hawthorn A. , Steinsiek R. , Leslie I.
Published: February 2024

The oil and gas industry is in a state of continually challenging the way to improve the efficiency and safety of well construction activities. An interesting path has been followed in the last 30 years in the development and use of logging while drilling tools. The measurement quality and reliability of these tools for open hole formation evaluation and geosteering has propelled an entire sequence of highly complex and highly deviated wells with enormous improvements in productivity from existing fields. You would be hard pressed to find any wells, particularly in the offshore domain, that do not utilize logging while drilling measurements that were once the province of wireline tools only. This development of technologies and tools has, as stated above, largely focused on open hole and while drilling applications only. The same cannot be said for cased hole evaluation tools in general, and for well integrity tools that measure the condition and properties of the casing and cement.

This paper will demonstrate the development of a new drillpipe conveyed tool that can both measure the casing condition and what is in the annular space behind the casing. We will show examples from around the world of the tools and the large variety of applications and conditions it has been deployed. Being able to run anytime drillpipe is deployed in the well therefore increases the amount of opportunity to get these critical measurements and also to be run in parallel with existing operations throughout the well construction period. As can be imagined this can lead to considerable efficiency gains as the logging does not require a dedicated run. The basic premise of the tool is that a drill collar is fitted with three circumferential pulse echo ultrasonic transducers. This allows for a full azimuthal image of the casing and annular space behind the casing if the tool is rotated, either from a downhole device such as a mud motor, or by surface rotation through the rig rotary table or top drive. The tool can be run in real-time and also in memory mode, in either case data is both processed downhole and the raw waveforms can be recovered from the tool when back on surface. Analysis of the acquired data allows for interpretation of internal caliper, the thickness of the casing, the location of casing collars and an evaluation of the material in the annular space behind the first casing string. The need to provide oriented images means the tool has magnetometers, accelerometers and a basic gyro measurement device that can be used for orientation of downhole devices such as whipstocks or oriented perforations.
Sequestration of CO2 from High CO2 Gas Field via Bicarbonate Solution for Microalgae Cultivation for Sustainable Biofuels
Authors: Shukor M. Syazwan , Onn M. Syazwan , Ghaddaffi M. , Nor M. , Mukhtar Faiz Azizi
Published: February 2024

It is anticipated based on study, that Natural Gas demand will increase by 65 percent by 2040 (IER, 2014). Hence, oil & gas industries are exploring technologies to unlocking the unconventional natural gas fields. Unconventional gas field contains mostly high contaminants such as carbon dioxide of up to 70 % and 30 % of hydrocarbons gas (Pellegrini et al.,2019). These contaminants can be sequestered in depleted offshore gas fields. However, this approach requires high pressure gas compression energy and availability of storage sites.

To resolve this issue, these contaminants can be sequestered as bicarbonate solution through the injection of carbon dioxide (CO2) into artificial seawater. The formed bicarbonate solution can be the feedstocks for the cultivation of microalgae (Ferreira et al., 2019) to produce sustainable biofuels, bioplastics and bio-based superfood. This method not only promote the effort to lower carbon emissions but also providing solution to enhancing the productivity of biomass production and contribute to the energy demand supply in the form of biofuels. Additionally, the sequestration of CO2 in the form of bicarbonates could benefit in terms of carbon tax savings which can benefit in overall techno economics.

It has been demonstrated through lab experimentation that by harnessing the power of photosynthesis from microalgae and integrating with bicarbonate solution, it has the potential to enhance algae growth and fixing more carbon to the algae as biomass. In conclusion, this novel approach can be the key in helping to reduce the amount of CO2 from extracted unconventional gas fields.
Antifoam Testing to Diminish Gas Entrainment in an Oil-Based Heating Medium
Authors: Lehmann Marc , Fisher Nicholas , Gloyn Mark , Brunt Steven , Tyers Sean
Published: February 2024

An oil-based heating medium (HM) system was found to have a high level of nitrogen gas entrained in the fluids due to the surge drum configuration located in-line with the process flow. The HM surge drum acts as an expansion vessel to account for volume changes when heating from ambient temperature to the operating temperature (260°C). The surge drum is pressurized by supplying nitrogen to reduce the vapor pressure and to maintain inert operating conditions, and is the coldest part of the circuit running between 140-160°C. The return flow from process and utility users was found to "waterfall" into the surge drum. Sampling of the heating medium at the suction side of the discharge pumps drawing heat transfer fluid (HTF) from the surge tank, showed that almost 20 vol% of the heating medium, at standard conditions was nitrogen gas. Modelling showed that the extent of nitrogen gas entrainment would be dependent on the fluid level in the surge tank and would likely originate from bubbles in the size range of 600-1200 microns exiting the Expansion Tank. Gas entrainment in the HTF at elevated operational temperatures is a significant concern that can lead to inefficient heating of the HTF and resulting in a loss of heating control to downstream users. A chemical treatment solution, using an PDMS antifoam agent, was explored to mitigate gas entrainment in the HTF. Foam reduction was observed when the HTF was treated with an antifoam in Foam Column tests. However, the PDMS antifoam agent showed no efficacy in reducing gas entrainment in a modified Ross-Miles Test. The contrast in results was attributed to the fact that the antifoam agent was able to rupture films when applied to actual HTF foam films, however when applied to entrained bubbles dispersed in the HTF, there are no films on which the antifoam can act on. It was concluded that mechanical options are far more likely to mitigate gas entrainment.
Near Well Supercritical CO2 Injectivity Study in Depleted Clastic Gas Field in Offshore Malaysia
Authors: Kashim M. Z. , Shah S. S. Md , Arof M. A. M , Harom-Haron Z. , Khairuddin K. , Tewari R. D.
Published: February 2024

PETRONAS is committed to reduce the bulk carbon dioxide (CO2) emission to the atmosphere by re-injecting the produced CO2 from high CO2 gas field to nearby identified storage site. One of the most important components to develop the storage site would be the understanding on the CO2 injectivity potential. Limited study is identified for near well CO2 injectivity research especially in determining the critical velocity rate to identify the injectivity potential during supercritical CO2 injection (scCO2). In this paper, the injection potential for Field D, which is in Offshore Malaysia has been studies for the storage prospect maturation purposes. Two representative sandstone samples with two distinctive permeability (~80 mD and ~300 mD) from the targeted injected zone in Field D were selected for the analysis. The initially brine saturated core sample was injected with scCO2 at fixed flowrate to establish the core at irreducible brine saturation. ScCO2 was then injected at slightly higher flowrate until the stable differential pressure is achieved. For each subsequent increases in flow rate, base rate of scCO2 is implied in the intervals to observe if there is any formation damage occurred in laminar flow regime. Relative Injectivity Coefficient (RIC) was also calculated using the returned rate differential pressure information. Furthermore, pre- and post-injection core characterization, using routine core analysis (RCA) and X-Ray CT-scan were conducted to examine any petrophysical alteration that might take place during the experiment. The critical velocity rate is then analyzed according to the differential pressure data which later upscaled to well-scale resolution. Based on the differential pressure trend from the two injectivity experiments, there is no clear evidence of formation damage even after the core has been subjected to high scCO2 lab flowrate (~110 cc/min). Only minor dissolution and fines flush-out was occurred. This observation is confirmed by pre- and post-scCO2 injectivity analyses comparison where the petrophysical changes is very minimal. Based on the evidence from differential pressure and pre- and post-sample characteristics, it can be concluded that the critical flow rates were higher than the maximum achievable laboratory flow rates. This denotes that there is no injectivity issues that is expected to occur up to upscaled well flowrate of 18.5 MMscf/day during the CO2 injection in storage target zone in Field D.
Exploratory Drilling of Multi-Layer Buried Hills with Complex Pressure in Deep Bohai Oilfield: A Case History
Authors: Zhang Xiaocheng , Li Wenlong , Xie Tao , Huo Hongbo , Xu Kun , Zhang Lei , Liu Hailong , Hou Xinxin , Liu Xun , Zhu Guojing
Published: February 2024

The exploration and development of Bohai Oilfield is gradually moving to the deep stratum. However, it is difficult to drill in the deep stratum due to complex pressure system and multi-layer buried hill. This paper analyzes the lithologic characteristics of the deep buried hill strata with complex pressure in Bohai Oilfield. Through the analysis of adjacent well data, seismic data and mud weight window prediction results, it is concluded that the main drilling risks in the surrounding area are leakage and overflow, and the key drilling technologies under the control of complex pressure are introduced, including well structure design, identify method of buried hill interface, drilling fluid maintenance, fine pressure control and other series of technologies. After a series of optimization design and technical application, the efficient drilling of complex pressure multilayer buried hill stratum is finally realized. This paper has a certain reference significance for safe and efficient drilling of deep complex strata in Bohai Oilfield.
Case Study on Retrofitted HEPA Filtration to Offshore Gas Turbine Inlet House and its Benefit
Authors: Shaharuddin Mohamed Arif Bin Mohamed , Hao Chai Jun , Vui Chow Kim
Published: February 2024

Gumusut Kakap semi-submersible Floating Production System (GK sFPS) is one of Shell operated deepwater asset in the state of Sabah, Malaysia. There are 3 production centers with water injection and gas injection facility. For gas injection facility, there are two units of gas turbine driving compressor barrels namely, HPC1 & HPC2. The gas injection facility serves as gas reinjection for reservoir management.

For gas turbine, preventative maintenance is required for water-washing the gas turbine internal components which is a gas generator prior to combustion. For GK sFPS, the gas turbine is an aeroderivative type gas turbine. Preventative maintenance is required due to dirt accumulated at the blades area (Naeem, Singh and Probert 2001). Water-washing period typically takes about 24 hours from shut down initiation, gas turbine cool-down period, water-washing activity, and starting up the unit again. Specifically shutting down HPC1 & HPC2, this involves system blowdown of the driven compressor barrels which incur flaring and impact to Green House Gas.

The intent of water-washing a gas turbine is to recover performance losses associated from dirt accumulation (also known as fouling) over time. The dirt accumulation is condition based on air quality filtration (i.e. filter efficiency) in filtering out dust, salts and other particles that affects gas turbine performance (Golbabaei, et al. 2013).
Smart Needle Valve: Intelligent and Cost-Effective Solution to Unlock Gas Production in a Tight Gas Field in China
Authors: Chen Zongpeng , Bo Jiangwei , Wang Xiangzeng , Lin Jin , Qiao Xiangyang , Wang Bing , Ding Yong , Qi Shiwei , Zhai Zhongbo , Wang Lang , Cai Xingxing , Fendt Andrew , Audrey Beryl , Kartoatmodjo Gayatri , Zhu Ming , Liu Yunlong , Wang Yunlong , Yang Weigang
Published: February 2024

Gas field C is an unconventional tight gas reservoir located in central China. As the gas wells mature, production rates start to decline because of the decreasing bottomhole pressure that prompts a liquid loading issue. The production loss is up to 114 MMscf/yr resulting from liquid loading. To mitigate this issue and hence optimize production, an innovative intermittent solution has been created. With the combination and implementation of cutting-edge artificial intelligence (AI) methods and Industrial Internet of Things (IIOT) technics, an automatic full-cycle closed-loop workflow has been achieved to manage the intermittent production dynamically. This solution has tremendous benefits in cost-effectiveness, efficient operations, health, safety, and environment (HSE) exposure reduction, bringing a new wave of digital technology to facilitate optimization in gas field operation. This solution is deployed in the wellsite IIOT gateway connecting both sensors and remote-controllable needle valve (RCNV) with edge computing technology. In design, the gateway processes high-frequency production data, completes a calculation, and then sends a command of "well open" or "well shut-in" to the RCNV. All these steps are managed by the gateway automatically within several seconds. Since 2022, the smart needle valve (SNV) solution has been successfully piloted for five wells with a 6% to 8% gas production incremental and 50% operational expense (OPEX) reduction. The application also reduces carbon dioxide (CO2) emissions and driving risk in the field by reducing personnel visiting the well pad.
Comparison of the effects of dexmedetomidine and nitroglycerin on cerebral oxygen saturation using near-infrared spectroscopy in patients undergoing controlled hypotensive anaesthesia: A randomised controlled non-inferiority trial
Authors: Rao J. Koteswara , Chhabra Swati , Mohammed Sadik , Bhatia Pradeep K. , Goyal Shilpa , Kumar Rakesh
Published: February 2024

Background and Aims:

There is limited literature wherein the hypotensive drugs have been compared to know the cerebral effects by monitoring regional cerebral oxygen saturation (rScO2). This study aimed to compare the effects of dexmedetomidine and nitroglycerin on rScO2 during controlled hypotensive anaesthesia using near-infrared spectroscopy (NIRS). The primary objective was to evaluate the non-inferiority of dexmedetomidine versus nitroglycerin in the occurrence of cerebral desaturation events (CDEs) during hypotensive anaesthesia.

Methods:

Adult patients scheduled to undergo head and neck surgery under general anaesthesia randomised to receive either dexmedetomidine or nitroglycerin infusion for controlled hypotensive anaesthesia. Cerebral oximetry was monitored with NIRS, and data regarding CDEs, bilateral rScO2, and peri-operative haemodynamics were collected. Continuous data were analysed using unpaired Student’s t-tests except for intra-group analyses, which were analysed using paired t-tests. Categorical data were analysed using the Chi-square test. For comparison of time to CDEs, Kaplan–Meier survival analysis with log-rank test was performed.

Results:

Of the 82 patients in both groups, CDEs were observed in 15 patients each. A decrease from baseline by 20% was observed in three patients: one in Group N and two in Group D. Statistically, there was an equal risk of getting CDEs in the groups. The time to CDE was comparable (P > 0.05). The difference in heart rate was statistically significant (P < 0.001).

Conclusion:

Dexmedetomidine is non-inferior to nitroglycerin in terms of the occurrence of cerebral desaturation events when used for controlled hypotensive anaesthesia in head and neck surgeries.