bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation of the Influence of Liquid Nitrogen on Tight Sands Through Micro-CT Scan Imaging
Authors: Al-Raeeini Khaled Ahmed Mohammed , Aljawad Murtada Saleh , Khan Hasan J
Published: November 2024

Hydraulic fracturing is essential for extracting hydrocarbons from tight sands but often results in suboptimal performance due to formation damage caused by water. Optimizing hydraulic fracturing fluid (HFF) with CO2 or N2 has led to only marginal improvements. This study proposes using liquid nitrogen to induce microfractures via thermal shock, reducing fracture initiation pressure through rock stress redistribution. A Scioto sandstone sample (5 mm in diameter) was heated to 70°C for 24 hours and then exposed to liquid nitrogen for 45 minutes. Changes in pore structure were captured using a high-resolution micro-CT scanner at a resolution of 2.4 microns before and after exposure. The image stacks were processed, and fifty-two cubic sub-samples (each 100x100x100 voxels) were extracted from four spots on the x-y plane and along the z-axis. These sub-samples were segmented into pore and solid grain regions using a machine learning algorithm, and the rock's porosity and permeability were calculated. Results showed an increase in average porosity and permeability from 15.4% and 6.3µD in the initial scan to 17.2% and 7.2µD in the final scan. Visual analysis revealed new pore spaces in the form of long channels, primarily near the outer boundary of the sample. These findings suggest that thermal shock induced rock stress failure, creating fractures that might reduce fracturing pressure. Using liquid nitrogen offers significant advantages, including preventing formation damage by converting to gas and flowing out easily. It also reduces the applied fracking pressure due to induced stress failure and serves as an environmentally friendly alternative to HFF, protecting water resources and avoiding disposal costs and contamination risks.
Identifying Critical Skills for the Future
Authors: Kashwani Hanan Abdulla , Rizvi Shaheena
Published: November 2024

With an ever growing emphasis on Sustainability, Abu Dhabi National Oil Company (ADNOC) continuously evaluates various aspects of operation to ensure our ability to navigate market dynamics. Over the last several years, our talent management practices have come under deep focus, and the transitions we have made has impacted the way we hire, retain and progress our people. The discipline approach to managing talent has provided far reaching insights into the capabilities we have and the depth to which we can invoke these capabilities.

In 2023, we embarked on yet another important transition – to identify and develop the Future Skills that we will require as we optimize our net zero journey. Given the shift towards digitalization, automation and integration of renewable energy, we are prioritizing upskilling future generations to keep ADNOC front and center of our industry.

We undertook this exercise in several phases, with the collaboration of our business leads and a Human Capital joint task Force. At its culmination, crucial data has been passed on to our businesses as well as key Human Capital functions for execution and alignment.

This project was divided into the following main stages: Benchmarking with global experts. Collating information through discussions, workshops and identifying a set of skills in areas e.g. Digitalization & Asset ManagementValidating skills with ADNOC Business Leaders and Experts. Creating, sanitizing and customizing skills and their definitions to create fit for purpose Future Skills.Existing Bench Strength. Identifying bench strength of all identified future skills through in-depth focus groups with Business Leaders and Experts to determine Build, Borrow, Buy strategies.Validating Future Skills. Conduct a group wide exercise to assess capability by deploying job specific future skill requirements, as well as mining data through self-declared skills.Integration with Workforce Planning, Talent Acquisition and other Human Capital Partners. To distill strategies to become part of the 5 year Business Plan (Build, Borrow, Buy).

The paper will deconstruct the process and also put forward the impact of this project and the steps that we undertook to deliver concise and usable output.
Study on the Key Factors Analysis and Measures Prevention of Casing Deformation in Horizontal Wells for Unconventional Reservoir
Authors: Zhang Wen , Dong Haihai , Ma Jifeng , Wang Xiaoguang , Zheng Sheng , Xu Hanbing , Ren Xu , Sheng Guorong , Zhou Wei , Zhang Ming
Published: November 2024

Based on the structural distribution characteristics and fracture development characteristics of block 530 in the Junggar Basin, Xinjiang, and by using microseismic, logging, and in-situ stress data, the characteristics of casing deformation in deep shale gas wells were summarized, the mechanism and main controlling factors of casing deformation were clarified, a risk assessment chart for casing deformation was established, and targeted risk prevention and control countermeasures were proposed. The research shows that fracture slip activation by fracturing is the main controlling factor of casing deformation. The fracture approach angle in the work area is mainly 10°-50°, accounting for 65.34%, and the critical activation pore pressure increment is 6.05-9.71 MPa. For casing deformation caused by geological factors, the prevention and control measures mainly include avoiding risky fractures and selecting low-stress mechanism factor areas for well placement. For casing deformation caused by engineering factors, the prevention and control measures mainly include four aspects: When placing wells, try to avoid high-activation-risk and high-slip-risk fractures. When it is impossible to avoid them, try to select areas away from the center of the fracture; Optimize wellbore parameters, adjusting the wellbore azimuth can reduce the shear stress acting on the casing to a certain extent and reduce the degree of casing deformation; Optimize the wellbore structure design, and ensure that the curvature radius of the horizontal well bending section is greater than 200 m on the basis of not affecting the drilling encounter rate of high-quality reservoirs; Optimize the fracturing operation parameters, increasing the avoidance distance, reducing the single-stage construction pressure, and increasing the stage length are effective measures to reduce the risk of casing deformation.
Leak to Fix: Emergency Pipeline Repair System (EPRS)
Authors: Alshhehi. Nayef Salem
Published: November 2024

The Abu Dhabi EPRS Club, which is composed of major UAE operators (ADNOC OFFSHORE, ADNOC ONSHORE, ADOC, BUNDUQ) that manage over 7000Km of critical pipeline assets in the region, relies on Emergency Pipeline Repair Service (EPRS) as a contingency measure. EPRS is a service that is established to intervene at short notice and to address any incident or damage sustained on subsea pipeline and cable assets that may affect the production and transportation of hydrocarbons. This service covers the ADNOC Offshore pipeline network of over 540 individual pipelines (>5000Km) with varying sizes from 4″-48″ that transport Oil, Gas & water from offshore fields to onshore facilities. The EPRS Club aims to ensure the safety and reliability of the pipeline infrastructure and to minimize the environmental and economic impacts of any potential pipeline failure.
Matrix Acidizing Treatments with Particulate Diverters to Enhance Stimulation Fluid Reach in Wells Completed with Inflow Control Devices
Authors: Gadelhak Abdulrahman , Mustafa Hammad , Li Sima. , Kelkar Shrihari , Bazuhair Ahmed , Almaazmi Mariam , Almenhali Marwa , Alhosani Hour , Enkababian Philippe , Ryan Abraham , Araque Gustavo , Elmasry Aly , Mahmoud Wael , Arali Vaishak , Kamaletdinov Bulat
Published: November 2024

A horizontal oil producer well, equipped with a complex dual completion configured with inflow control devices (ICD) and a pre-perforated liner (PPL), situated in an offshore Middle East carbonate reservoir, underwent stimulation using HCl combined with a self-degradable multimodal particulate diverter (PD). The purpose of the PD was to bridge the ICD intervals and significantly redistribute the acid fluid flux from the high-injectivity ICD intervals to the lower-injectivity PPL, maximizing the reach of stimulation treatment fluid to enhance reservoir coverage.

PDs have been successfully used to achieve diversion in cased and perforated completions for years. However, PDs have rarely been used in ICD completions because the ICD design typically ensures even distribution of acid across the completion. In this case, a significant permeability contrast between the ICD-heel interval and the PPL-toe interval necessitated the PD application. Injected particulates bridged the ICD nozzles, diverting acid flow towards the lower-permeability wellbore section. To validate this method, a proof-of-concept yard test with an ICD tool string calibrated the necessary particulate volume, while laboratory testing verified PD degradation under reservoir conditions. Near-wellbore modeling indicated that introducing a PD stage ahead of the main acid stage could temporarily divert acid from the heel to the toe compartments, resulting in a more uniform wormhole length and stimulated skin profile.

The PD was successfully pumped into the ICD liners, and during treatment injection, diversion was confirmed through the pressure response. Upon the first pill landing, the PD stage generated over 400 psi of diversion pressure in the heel compartments, affirming the bridging of the ICD nozzles. Subsequently, when the second pill reached the ICD section, bottomhole pressure remained stable, indicating complete bridging by the first pill. Stimulation acid was effectively diverted and injected into the PPL compartment of the well. The post-stimulation production logs verified the success of the stimulation, demonstrating a more uniform distribution across the entire horizontal drain, despite the permeability contrast between the heel and toe compartments.
Performance Evaluation of Seawater-Based Fracturing Fluid with High-Viscosity Friction Reducer and Different Polymers
Authors: Alessa M. M. , Alarifi S. , Murtaza M. , Aladi A.
Published: November 2024

Hydraulic fracturing, especially when employing water-based fluids, demands a substantial amount of water resources. Given the scarcity of freshwater sources in Saudi Arabia, the utilization and transportation of freshwater for hydraulic fracturing operations have become excessively expensive. Since 2012, efforts have been underway to explore the feasibility of utilizing seawater (SW) as the main component for fracturing fluid in Saudi Arabia. The paper aims to utilize seawater to replace freshwater as the base fluid in slickwater.

The study conducted a total of 22 experiments comparing DI water-based slickwater and seawater-based slickwater in different High Viscous Friction Reducer (HVFR) concentrations. After selecting the HVFR concentration with the best rheological performance in seawater, two polymers which are HPG and CMHPG were tested before the addition of Zr-Crosslinker using Anton Paar-MCR 702e high-pressure, high-temperature (HTHP) Rheometer under a consistent pressure of 500 psi, a shear rate of 100 1/s, and varying temperature conditions (70°C and 120°C).

In the first part of the study, different concentrations of HVFR were tested in both DI water and seawater (SW) at 70°C and 120°C. In SW, at 70°C, two of the concentrations showed promising results, while at 120°C, neither concentration maintained reliable viscosity. Conversely, all concentrations performed well in DI water. After adding the two polymers, HPG showed decreasing stability at higher temperatures in DI water. In contrast, at elevated temperatures, CMHPG exhibited greater stability compared to HPG and generally demonstrated higher viscosity. It was observed that in DI water, HPG is always the dominant polymer. On the other hand, in SW, at lower temperatures, HPG outperforms CMHPG in terms of viscosity and stability. However, at higher temperatures, CMHPG is the better polymer. Additionally, after adding the Zr crosslinker, viscosity and stability were improved for both polymers.

This paper presents novel insights into the utilization of seawater as a base fluid in slickwater hydraulic fracturing operations in Saudi Arabia. By comparing the rheological performance of seawater-based slickwater with freshwater-based slickwater, and exploring the effectiveness of different polymers and crosslinkers in seawater environments, this innovative strategy offers significant potential for economic savings while promoting sustainable water management practices in the petroleum industry.
Microstructural and Petrophysical Properties of Fault Rock from Outcrops in the United Arab Emirates
Authors: Al Hashemi Hussain H. , Fisher Q. J. , Yielding G.
Published: November 2024

There are many studies covering the RAK and Al-Ain area, but most of these studies focus on sedimentology, sequence stratigraphy and some structural events were conducted by ADNOC, ExxonMobil and PDO in the north of Oman. To date, no comprehensive field study of fault sealing has been conducted on these outcrops or in any place in the UAE. Fieldwork was undertaken in the valley/Wadi Rahabah, Wadi Al Bih and Jabal Hafit, which provides a good analogue for the fault in the Shuaiba, Thamama and Khuff reservoirs in the Abu Dhabi Onshore (OS) field. The results provided evidence that all fault rocks from outcrop exposures could act as conduits in the damage zone (DZ) and baffles in the Fault core (FC). The permeability contrast between fault and host within the reservoir suggest that all fault rocks from outcrop exposures could act as baffles in the DZ and seals in the FC. The FC is cut by open fractures, and thickness varies significantly over a short distance in the outcrop. If such fractures are present in the subsurface, they could allow the DZ to act as a conduit to flow and the fault could act as a baffle. The variation in the FC thickness ranges from 2 cm to 0.5 m within a short distance of around 10 m. In addition, the ranges span from 4 to 30 cm within a short distance of around 2 m from different outcrops, limiting the extent to which the FC can act as a seal. Three types of microstructural textures of FC were found in the UAE outcrops: first, a breccia located in the Jilh formation; second, a micrite-dominated located in the Khuff formation; and third, calcite cement located in the Shuaiba and Rus formation.
Prediction-to-Production: Implementing Machine Learning for Behind Casing Opportunities
Authors: Zaizakrani M Farid , Suali Dvercillia , Sidek Sulaiman , Surin Nicholas Aloysius , Jeffry Suzanna Juyanty M , Shah Jamari M , Hazali Nurdini Alya , Mokhlis Mohamad Mustaqim , Muniandy Satyaraj , Saifuddin M Nabil
Published: November 2024

In the Oil and Gas (O&G) industry, maximizing production from existing wells is crucial to staying competitive. Identifying and accessing Behind Casing Opportunities (BCO) for Production Enhancement and Idle Well Reactivation (PE-IWR) initiative, provides a cost-effective alternative than drilling new wells to increase the recovery and extend the life of a well. However, accurately predicting BCO in mature offshore fields, particularly in Field S located in offshore East Malaysia, remains a formidable challenge due to complex geological formations, remote locations, and aging infrastructure which have resulted in ambiguous logging results and high operational costs that complicate data collection and reduce the reliability of conventional logging methods.

The purpose of this paper is to discuss an innovative approach to predict BCO by leveraging Artificial Intelligence and Machine Learning (AI-ML) as a pre-screening tool for identifying PE-IWR candidates, showcasing a comprehensive analysis and method to validate the accuracy of the result predictions using Field S as case study. The BCO identification solution has expedited the discovery of multiple promising candidates, from previously untapped areas, resulting in a swift realization of its benefits and has made the decision-making process much easier. One case that stands out is the discovery of promising BCO in Well-01 of Field S, which indicated significant potential oil gain. A collaborative effort between the engineers and Subject Matter Experts (SMEs) was initiated, with the assistance of the solution, to quickly capitalize on this opportunity that involved comprehensive subsurface technical assessment, including detail analysis of well logs, investigation of well intervention and integrity history, evaluation of reservoir performance, and review of well production behavior.

The successful implementation in Field S, marked another favorable outcome that demonstrates the effectiveness and practicality of the AI-ML solution in enhancing BCO identification to optimize production performance and increase profitability. These implementations not only empower engineers to uncover hidden reservoir potentials but also foster a proactive approach to well and reservoir management and surveillance through real-time data driven approach.
A Digital Platform to Overcome Challenges when Analyzing Real-Time Drilling Performance with Surface Rig Parameters
Authors: Falini E. , Brillaud L. , Mahjoub M. , Menand S.
Published: November 2024

The opportunity to improve drilling performance can be capitalized on, by timely and accurate representation of the physics applied to the bit while drilling. The mechanical specific energy (MSE) has usually been used to recognize potential drilling dysfunctions, unfortunately, without direct downhole measurements, this indicator is often poorly estimated. Real-time measurements such as weight-on-bit (WOB), torque-on-bit (TOB) and motor differential pressure, among others, can be obtained downhole and transmitted to surface while drilling with specialized tools, and when high data density is required, these tools are deployed with wired pipe. The cost associated with these technologies are hard to justify for the vast majority of development work around the world. In many cases, only surface measurements are available in real time, but these measurements are subject to several sources of bias, which if not properly processed, could lead to wrong interpretations. Due to these limitations, downhole drilling parameters could be better determined with algorithms. The goal for this publication is to explore the challenges faced when using drilling surface data and propose a new methodology to improve real-time identification of drilling dysfunctions.

The first step of the process consists in, using surface measurements to identify and categorize at any given time, every single operation taking place at the rig. This rule-based algorithm segments the operational sequence, then takes surface measurements from several operations to automatically derive downhole drilling parameters such as WOB, TOB, and/or motor differential pressure. Finally, the MSE and other indicators such as drill strength (DS) are calculated and intuitively displayed to evaluate current drilling performance, facilitating the implementation of optimum drilling parameters.

Miscalibrations of weight-on-bit and differential pressure was identified after analyzing several past wells datasets, and in most of cases, torque-on-bit was missing. By applying the algorithm, accurate recalculation of these downhole drilling parameters from surface data was performed. The results after the recalibration, showed a very good correlation with actual downhole data, when compared to available measurements captured with downhole BHA sensors. Moreover, these accurate results were then used to identify drilling dysfunctions and to recommend optimized drilling parameters for the next well. Additionally, this methodology is used in a real-time operating center, advising rigs with ongoing drilling operations.

This algorithm, not only allows accurate estimation of downhole drilling parameters in real-time but, can also be applied to old datasets from offset wells. By removing human calibration errors, this methodology enables better understanding of the physics occurring at the bit. As our industry makes progress into drilling automation, this new model promotes consistency and performance.
Numerical Analysis of Hydro-Mechanical Behavior of Faults: Impact of Hydraulic Conductivity Variation on the Pressure Buildup Due to Co2 Injection
Authors: AHN Kyeunghye , BOURGEOIS Frederic , POUYA Amade
Published: November 2024

This study aims to create a advanced numerical model to estimate the effect of fault reactivation caused by carbon dioxide (CO2) injection on the pressure field in nearby rock formations. The study also evaluates the hydro-mechanical stability of adjacent faults under different pressure conditions during underground CO2 injection. The investigation explores the hydro-mechanical response of faults, especially the changes in hydraulic conductivity with fault opening and how they influence fault reactivation.

Our methodology uses zero-thickness interface elements in a Finite Element Method, with adequate constitutive model, to precisely simulate single-fault planes behavior during coupled hydro-mechanical processes. This approach improves existing models in rock mechanics by allowing accurate sensitivity analysis of fracture transmissivity to normal stress variations and shear displacement. We incorporate Poiseuille's cubic law and also thin layer model law to account for changes in hydraulic conductivity due to mechanical deformation. The fault mechanical behavior is described using an elasto-plastic nonlinear model, which effectively captures the complex interdependencies between elastic and plastic strains under variable stress and fluid pressure conditions.

Using the Finite Element software, our numerical simulations provide important insights into the behavior of faults under seismic and aseismic conditions induced by CO2 injection. The study investigates various injection scenarios, focusing on the pressure buildup and subsequent dissipation during rest periods, with particular emphasis on the interaction between fault and reservoir permeabilities. Our findings reveal significant variations in pressure dissipation patterns, depending on the mechanical properties and initial permeability of the geological formations. These results contribute to a deeper understanding of pressure distribution dynamics and fault reactivation processes, offering valuable implications for managing induced seismicity in CO2 sequestration projects.

This study presents a new and comprehensive modeling approach to estimate fault reactivation and its hydro-mechanical consequences within CO2 injection contexts. By integrating mechanical and hydraulic factors in fault behavior analysis, the research enhances our understanding of fault responses to induced pressures, thereby aiding in the development of more effective risk assessment and mitigation strategies. The introduction of advanced numerical techniques and detailed sensitivity analyses provides a robust framework for future studies on fault stability and induced seismicity.
Flow Performance of Two-Phase Fluid in Carbonate Fractured-Vuggy Media under HTHP Conditions
Authors: Sun K. , Zhang G. , Jiang Q. , Fu J. , Liu Q. , Li R. , Jia W. , Zhang M. , Kong L.
Published: November 2024

In the middle-late stage of depletion development, water influx and channeling are usually unavoidable in deep carbonate fractured-vuggy reservoirs, which leads to a rapid increase in water cut of production wells, thus significantly reducing the total oil recovery. This study focuses on flow performance of oil and water in carbonate fractured-vuggy media under high-temperature and high-pressure conditions, the two-phase flow characteristics of porous vs. porous-fractured media and fractured vs. fractured-vuggy media are investigated and compared respectively based on lab tests. It is found that oil recovery of waterflooding in the porous-fractured media is only 37.36%, which is much lower than that in the porous media (60.69%), indicating that the presence of fracture can greatly reduce the co-seepage time of oil-water and result in a decrease of total oil recovery. The oil recovery of the fractured and fractured-vuggy media is 85.97% and 53.09%, respectively. The quite obvious difference shows that when the injected water flows into the vug structures along the fracture at a pretty low speed, only part of the oil can be displaced out by the effect of gravity differentiation. The other rest of oil would be widely distributed in the upper part of the vug structures and sealed as remaining oil, which is quite difficult to be driven out. This study reveals the flow law of two-phase fluid in fractured-vuggy media under HTHP conditions, providing novel insights into flow mechanisms of carbonate reservoirs with different scales of flow and storage structures.
Analysis of Clustering Machine Learning Algorithms and Generative Artificial Intelligence Tool for Visualization and Interpretation of Seismic Data
Authors: Supekar N. , Peddada S. , Reid J.
Published: November 2024

Seismic attribute analysis is often confounded by the complexity of the subsurface. Clustering machine learning algorithms reduce complexity and bring the most salient features of the seismic datasets to the fore. By conducting a comparative study of clustering algorithms applied to 2D seismic data, we can determine a set of optimal methods for visualizing particular seismic attributes. This paper presents an analysis of clustering algorithms, and a generative artificial intelligence-based large language model (LLM) customized for interrogating seismic data.

Based on data partitioning, density and distribution category, K-means, DBSCAN, and Gaussian Mixture Modeling (GMM) algorithms were used to analyze amplitudes in 2D stacked seismic data. To assess cluster quality, performance metrics such as the Silhouette index and Davies-Bouldin Index were determined. The analysis revealed that seismic data can be effectively divided into clusters based on the amplitudes and frequencies along each of the traces and times. These clusters allow interpretation geophysicists to readily identify potential geohazards such as shallow gas, faults, or other amplitude anomalies. It was observed that K-means successfully divided the data into clusters in a manner which was sensitive to the overlapping data and noise. GMM exhibited a probabilistic feature of partitioning the data effectively. DBSCAN and GMM provided well distributed and identifiable clustering and fitting of amplitudes.

The choice of clustering algorithm depends on the data size, data complexity, and performance metrics. Clustering is often regarded as a foundational technique in various types of data analysis. It may allow interpretation geophysicists to readily discern prominent and physically relevant amplitudes, amongst other seismic attributes. Further work, detailed in section 2 of this paper, focuses on developing a generative AI-based model that can function as a custom-made domain-interacting tool. This serves as a basis for developing additional tools through fine-tuning and additional training of AI models. These models then can be trained to predict subsurface structures and help processing/interpretation geophysicists to review and understand seismic data from a different perspective.
Scaling Autonomous Inspection Robots For Industrial Facilities: Challenges and Opportunities
Authors: Gjerde K.
Published: November 2024

Autonomous inspection robots have emerged as pivotal assets in enhancing operational efficiency and safety within industrial facilities. This paper explores the challenges and opportunities in scaling the deployment of such robots across diverse industrial environments.

Firstly, we delve into the technological advancements driving the evolution of autonomous inspection robots, including sensor integration, machine learning algorithms, and real-time data processing capabilities. These advancements enable robots to navigate complex environments, detect anomalies, and perform detailed inspections with high accuracy.

However, scaling the deployment of autonomous inspection robots presents multifaceted challenges. These include the need for robust infrastructure to support fleet management, efficient recharge, and seamless integration with existing industrial systems. Additionally, ensuring compliance and addressing cybersecurity concerns are imperative for widespread adoption.

Despite these challenges, the benefits of scaling autonomous inspection robots are substantial. Enhanced operational efficiency, reduced downtime, and improved worker safety are among the primary advantages. Moreover, by leveraging data collected by these robots, industries can make data-driven decisions, optimize maintenance schedules, and prevent costly equipment failures.

In conclusion, while scaling autonomous inspection robots in industrial facilities presents complex challenges, the potential benefits outweigh the hurdles. By addressing these challenges through interdisciplinary collaboration and technological innovation, the widespread deployment of autonomous inspection robots can revolutionize industrial operations.
Analyzing Methane Emissions Using Satellite Imagery and Artificial Intelligence
Authors: Schillaci Guido , Fiorucci Marta , Bonacchi Luigi Bono , Pencelli Manuel , Politano Andrea , Agostino Antonino , Pau Daniele , De Magistris Giovanni , Hanjra Raman , Sachdev Dheeraj , Parrella Ilaria
Published: November 2024

Methane has a significant impact on climate change as it is a potent greenhouse gas. The energy sector is responsible for 30% of methane emissions worldwide. Effective and continuous monitoring and mitigation of methane emissions are crucial in mitigating the increase of global temperatures. However, current methane emissions monitoring technologies present challenges due to their reliance on the deployment of sensors and personnel near the emission sources, which can be difficult and costly, particularly in the case of large-scale and remote industrial facilities such as those in the energy sector. Methane emissions from these facilities can span vast areas, making traditional monitoring methods time-consuming and resource intensive. Therefore, there is a pressing need for advanced technologies that can provide accurate and real-time methane emissions data from remote and hard-to-reach locations.

The dispersion of methane over large sites poses challenges in the emission measurement and quantification. Satellite imagery, such as those provided by the National Aeronautics and Space Administration (NASA) or by the European Space Agency (ESA) with the Copernicus program, can provide a global map of methane concentrations every day. However, interpreting and analyzing such data is still an open challenge.

The contribution of this work is multifold. First, it analyzes how the adoption of artificial intelligence and computer vision techniques can support the monitoring and quantification of methane concentrations from satellite imagery, with the aim of supporting mitigation activities for reducing methane emissions. State-of-the-art computer vision and artificial intelligence methods for methane emission quantification using satellite imagery are reviewed. A particular focus is given to methods for enhancing the accuracy of methane quantification using satellite imagery, and for addressing the lack of ground truth data for assessing the quality of the measurement.

Second, this paper provides a review of existing data sources for methane emission monitoring and quantification. Satellite imagery datasets from public and private entities are reviewed, as well as tabular datasets that contain processed information from satellite imagery about methane emitters and their geographically referenced information.
Renewables for Subsea Power – Successful Completion of Transformational Low Carbon Subsea Power Project
Authors: Slorach P. , Robertson G. , Douglas A. , Crossland I. , Retzler C. , Money N. , Birch Michael
Published: November 2024

The Renewables for Subsea Power (RSP) project is a first-of-its-kind commercial-scale demonstrator project, presenting a novel way to provide fully autonomous offshore power generation from renewable energy, delivering a cost-effective and flexible alternative to power and communications from shore for operating subsea equipment. The project showcases how net zero can be enabled in an offshore environment through the reduction of greenhouse gas emissions associated with power delivery to assets.

RSP has completed a three-phase program to demonstrate the delivery of low-carbon power and communications to assets offshore. After competition of Phase 1 (a detailed front-end-engineering-design (FEED) study) in 2021, Phase 2 consisted of system communications bench testing, assembly of the subsea systems, and onshore commissioning of both the wave energy device and energy storage system.

Phase 3 included integrated system deployment off the coast of Orkney in the UK North Sea, combining a wave energy converter and seabed energy storage system for local, reliable subsea power and communications delivery to a subsea electronics module and a residential underwater vehicle.

This paper builds on the findings of SPE-216124 (Slorach et al., 2023) with particular focus in this paper given to the demonstration of power export to the subsea energy management system, which provides power to both subsea controls equipment and the underwater vehicle residency. This has been demonstrated through a remote wireless communication link to the subsea equipment.

The conclusion of the at-sea trials has provided evidence of the benefits of directly integrating renewable power into subsea systems. The offshore trial has also provided invaluable lessons learned from over a year of at-sea operation, covering an extensive testing regime including all aspects of seasonal environmental impact on the equipment. These will lead to commercial deployments planned for 2024/5.
A Unified Modelling Approach using AI based Probabilistic Method to Address Structural Uncertainty in Carbonate Reservoirs
Authors: Grover Anurag , Al Shamsi Saif , Ahmed J. , Al Mesmari Abrar , Sandjivy L. , Collet Mickael
Published: November 2024

Structural uncertainty is the degree of variability or error in the interpretation of subsurface geology, especially the geometry and position of the reservoir. It affects the estimation of hydrocarbon volume and the design of the optimal field development plan. In complex and heterogeneous carbonate reservoirs, structural uncertainty can be significant due to factors such as velocity variations, seismic resolution, multiple scenarios, and human bias. Therefore, it is crucial to have a robust and efficient workflow to quantify and reduce structural uncertainty using all available data sources. One of the challenges in conventional structural uncertainty workflows is the reliance on deterministic methods that often produce a single or few scenarios based on subjective assumptions and manual adjustments. These methods are time-consuming, inconsistent, and difficult to validate. Moreover, they do not account for the uncertainty in the seismic data quality and processing, which can propagate and affect the reservoir model. A more rigorous and objective approach is needed to capture the full range of possible structural outcomes and their probabilities.

This study proposes an integrated stochastic structural workflow that leverages Artificial Intelligence (AI) techniques to generate multiple realizations of the reservoir structure and quantify their uncertainty. The workflow consists of four main steps: (1) generating an initial structural model based on seismic and well data, (2) applying an AI-based probabilistic method to estimate the combined uncertainty (horizon interpretation & velocity) and its impact on the depth conversion, (3) performing a stochastic simulation to sample the combined uncertainty distribution and generate multiple depth-converted structural models, and (4) evaluating the structural uncertainty ranges and their implications for the reservoir characterization, volumes {Gross Rock Volume (GRV) & Stock Tank Oil Initially In Place (STOIIP)}, and field development plan. The workflow is applied to a case study of heterogeneous carbonate reservoirs in the Middle East, and the results are compared with the conventional deterministic methods for capturing depth uncertainty.
Green Growth and Sustainable Development on the Way: A Case Study from Fracturing Campaign in South Sulige Gas Field
Authors: Ting Jin , Fuyang Wu , Qian Ma , Yifan Dong , Qiang Wang , Na Li , Guan Wang , Liang Zhao , Jing Hua , Shu Zhang , Yin Luo , Yunlong Fu , Chao He
Published: November 2024

The South Sulige gas field is located in the middle of the Mu Us Desert in Inner Mongolia, with an arid climate, sparse vegetation, scarce water resources, and a fragile ecological environment. As the main operator in this field, South Sulige Operating Company (SSOC), a joint venture company between CNPC and TotalEnergies, aims to accelerate its transformation to green growth and sustainable development by reducing water consumption and carbon emissions in the fracturing campaign.

This paper describes a novel flowback-water treatment process, which can quickly treat the post-fracturing flowback water onsite with satisfactory water quality, required treating rate, and minimized cost. The treated flowback water will be used for mixing guar gel and fracturing in offset wells of the same pad. In addition, a specially designed gas capture and recovery unit is installed on the wellsite. Natural gas could be directly discharged into the downstream production network during the well cleanup period. Furthermore, an attempt was also made to substitute a traditional diesel fracturing pump with an electric-drive fracturing pump using the state grid.

Reuse of flowback water can reduce water consumption and waste disposal, which is critical for deserts and grasslands. Unlike the simple practice of treating flowback water to mix slickwater for pump-down in the adjacent blocks, remixing guar gel is required to place a high concentration of proppant and thus keep high post-fracturing production performance. The laboratory analysis result shows that the key ions in the treated flowback water meet the requirement for mixing gel. The core damage test also shows an equivalent level between treated flowback water and clean water. The maximum daily treating rate for one treating package was 700 m3/day and clean fluid yield rate was 80%. The yearly flowback water reuse ratio reached 40% and roughly saved 14% of the entire water consumption. On the other hand, a large volume of natural gas was captured after the special recovery units were utilized for a total recovery time of 5073.8 hours in 2023. Also, electric-drive fracturing pumps were used in 58 wells, which was 47.5% of the yearly work scope. These efforts resulted in approximately 76,900 t carbon emission reduction for the last fracturing campaign.

In the development of a tight gas field, to produce industrial gas flow from target wells, hydraulic fracturing is usually required. With more attention paid to environmental protection worldwide, how to balance project profitability with resource consumption and carbon emissions has become a critical consideration in the hydraulic fracturing domain. The practices described in this paper may be well adapted to other blocks with similar development features.
Chemical Remediation of Excessive Water Production
Authors: Othman A. , Ali A. , Kamal M. S. , Aljawad M. S. , Al-Ramadan M.
Published: November 2024

Excessive water production in oil wells diminishes their operational lifespan and presents notable technical and economic problems, including corrosion, less oil production, and scaling. These challenges are addressed with chemical techniques such as polymer-gel treatments and nano-silica which isolate water pathways within rock formations. These systems form gels upon contact with water but disperse when exposed to oil. The primary objective of this work is to develop polymer and nano-silica gels and compare their performance at reservoir conditions.

In this paper, we conduct a comparative study of two systems used to remedy the wells with excessive water production. Rheology and visual inspection are employed to assess the gels and gelation time formed by both systems. Various formulations of emulsified polymer-crosslinker and nano-silica systems, are inspected through rheology and tested in core flooding experiments. The better emulsifier is selected and added before the polymer, to help in diverting the mechanism to the water zone. The emulsifier tends to form emulsion and raise the viscosity of the oil zone. Then the pH of the system rose followed by the addition of polymer and crosslinker. In the nano-silica system, the breakers and activators are assessed to get the efficient system used in the study. Improved systems are proposed and tested alongside oil to explore breaking mechanisms. Then, core flooding experiments were conducted at 94 °C, 2000 psi confining, and 400 psi back pressure to evaluate the efficiency of the old and improved systems.

The visual and viscosity experiments identified the optimal concentrations of copolymer and nano-silica, tested both with and without oil, and suggested a better replacement. Based on the rheology results, appropriate concentrations of the activator and breaker were recommended for each temperature level to be used in core flooding evaluations. In these experiments, the selected concentrations significantly reduced water production across all types of core plugs tested. Following treatment, the emulsifier polymer crosslinker and nano-silica have a specific range of maintained structural integrity under varying temperatures and pressure differentials. The proposed system combination effectively inhibited water flow in different types of core samples by gelling the water zones and filling fractures and pores that directed water flow.

Both proposed systems impede water flow while forming emulsions with oil, which allow the passage of oil. However, the long-term integrity needs to be assessed to have a better view of the system, besides the cost of the two materials. This study emphasizes the viability of different innovative systems as a practical chemical solution to manage excessive water production in oil wells with significant pore openings.
BOP Pressure Chart Analysis Using Computer Vision Technology
Authors: Al Hosani Ali Mohamed Sayyar , Selvamoorthy Geetha , Kumar Koushik
Published: November 2024

A blowout preventer (BOP) is critical safety equipment in drilling operations, designed to prevent the uncontrolled flow of liquids and gases. BOP systems require inspection and testing at least every 14 days, with a pressure test conducted to ensure their condition. This test currently involves manually decoding pressure chart data from a mechanical pressure chart recorder, a time-consuming process. Our solution automates this by capturing the image of the pressure chart and decoding it using AI image analysis.

The application integrates with an existing BOP Inspection application. The drilling supervisor takes a picture of the pressure chart, which is then processed by an image processing algorithm. The solution includes techniques like grid and trace splitting, color detection, trace pixel classification, template detection, text extraction and recognition, template matching, outlier removal and pressure value analysis.

This automation saves an average of 90 minutes per test for the drilling supervisor and improves the accuracy of pressure test reporting. Applied across ADNOC Onshore rigs, it has shown an estimated 300% ROI. The extracted data is exported in JSON format for integration with existing applications.

This paper presents a novel application of AI in computer vision for automating this pressure chart data extraction, demonstrating significant efficiency gains and a high ROI, adding value to the petroleum industry's body of knowledge.
Effect of Fracture and Vug Network on the Dolomite Carbonate Acid Stimulation Process
Authors: Jia Cunqi , Alkaabi Saif , Hu Jinchuan , Sepehrnoori Kamy
Published: November 2024

Acid stimulation in carbonate rocks represents a classic example of reactive flow in subsurface porous media and is also an extremely effective improved oil recovery technique with broad applications. The acid solution is injected into the formation under the formation fracture pressure to increase formation permeability while bypassing damaged domains around the wellbore. This work extends an integrated two-scale continuum model that contemplates mass, momentum, and energy changes to study the acid stimulation process in complex carbonate acid stimulation systems with the development of fracture and vug networks. Numerical examples are designed to examine the impact of isolated fracture and vug parameters on the results of acid stimulation. Results show that the improved two-scale continuum model offers a novel method for describing the momentum transport of fluids within complex media. It eliminates the necessity of introducing and determining additional physical parameters through numerical simulations and experimental research. The presence of isolated fractures and vugs has a limited contribution to the hydraulic parameters of permeability. Isolated fractures and vugs reduce the consumption of acid fluid required to break through the target core sample but do not change the optimum injection rate for wormhole formation. The development of fractures and vugs can guide the development pathways of wormholes within the matrix core but does not alter the dissolution patterns corresponding to the specific acid injection rate.