bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Water-Swelling Agents with a Function of Programmable Self-Destruction for Well Killing Operations in Oil and Gas Condensate Fields Complicated by Fractures and Abnormally Low Reservoir Pressure
Authors: Mustafin A. , Varfolomeev M. , Pavelyev R. , Bolotov A. , Minkhanov I. , Kalmeteva R. , Mirzakimov U.
Published: November 2024

This work presents a water swelling agent with a function of "programmable" self-destruction for reservoirs complicated by fractures, and investigates the possibility of its application for well-killing operations, where conventional agents are ineffective.

At the first stage, the synthesis of water swelling gel particles formulations was carried out, taking into account the selection of crosslinker to achieve "programmable" self-destruction of the formulation after a certain period of time. Then, works were carried out on selection of optimal formulations on the basis of study of swelling coefficient, long-term stability, self-degradation time, rheological parameters and blocking properties under different salinity conditions and compared with current commercial agent. The efficiency of the compositions was determined on the basis of wellbore modeling system under reservoir conditions to analyze the blocking efficiency of gel particles in real time.

Synthesis of samples based on different crosslinker monomers, initiators, and modifiers (79 compositions) were carried out, which allowed us to develop a composition with optimal degradation dynamics, capable of being stable for 7 days and further self-degrade at 40 °C and salinity of 3.6 g/L (grams per litter), have a low density and are compatible with reservoir fluids. All samples, have corrosion rates up to 0.1 g/m2·hour (grams per square meter hour) and characterized by a high strength factor for 7 days. After this period, the parameter decreases due to the beginning of degrade. The results of studies of rheological characteristics of blocking compositions indicate that the synthesized samples show high values of static and dynamic shear stress more than 62 Pa (pascal). According to the results of studies, on the HTHP filter press, it can be concluded that the synthesized particles are characterized by sufficiently high blocking properties, capable of creating a fracture aperture 0.2 mm (milimeters) opening and low ability to penetrate, less than 4 ml of liquid has been filtered during experiment. According to the results of filtration studies, the synthesized gel particles can effectively block the model of an idealized fracture, 0.1 mm opening up to pressures of 63 bar, making this system a great potential for well killing operations in reservoirs complicated by fractures. Based on the results of laboratory tests, the developed particles can be recommended for further pilot tests.

Generally, the developed water swelling gel particles with "programmable" degradation showed high efficiency of blocking and reduction of well development costs. This allows expanding the application to well killing operations for abnormally low formation pressure reservoirs complicated by natural fractures.
Can 3D Seismic Assist the Subsurface Characterization of Low Permeability Reservoirs? A Western Canada Case Study
Authors: Abaco Christian , Jowett David , Baniak Greg
Published: November 2024

The appraisal and development of low permeability reservoirs require detailed knowledge of their quality and spatial variation. Different applications of 3D seismic data are used to map reservoir's property variation for subsurface characterization, including structural analysis, reservoir property mapping and seismic lithofacies prediction.

Seismic structural attributes were used to map large structural features that compartmentalize the reservoir and to identify enhanced natural fracture zones that may locally increase reservoir's permeability (‘sweet spots’). The prestack AVO and rock physics inversions are used for geomechanical properties calculations and total porosity and mineral fraction volume estimation. The inversion results were further extended for reservoir stress computation including pore pressure and effective stress estimations calibrated to pore pressure and DFIT measurements. Reservoir lithofacies volumes were generated using machine learning workflows and direct probabilistic inversion outputs, with the results generally matching the reservoir's lithology mapped from the core data.

Moving forward, the 3D seismic data can successfully assist the subsurface characterization of low permeability reservoirs and can be used to support well placement and to optimize the drilling and completion operations.
Recent Findings from Ongoing Surveillance Using Time-Lapse Walkaway VSP Monitoring of CO2 WAG EOR Project in an Onshore Field in Abu Dhabi
Authors: Mohamed M. , Ahmed J. , Waqas M. , Alhamedi A. , Gupta S. , Dogra S. , Albulushi A. , Guerra R. , Ali S.
Published: November 2024

Time-lapse seismic is an essential tool for reservoir monitoring. However, using 4D seismic in carbonate reservoirs poses some difficulties because of rock's nature. Time-lapse Walkaway VSP surveys were carried out on an onshore carbonate field in Abu Dhabi, which included Baseline and three Monitor surveys. The surveys aimed to track the fluid-front due to the CO2 WAG injection, and to assess repeatability between sources and receivers and associated 4D signal. The recent Monitor-3 survey was acquired after 6.5 years of CO2 WAG injection post the Baseline survey. This paper discusses results from the Monitor-3.

The acquisition geometry was same for all the surveys, however for Monitor-3 the source offset was extended to 5km from the wellhead to refine the anisotropy model to improve the final image. The data revealed good repeatability between the Baseline and Monitor-3 surveys. A processing workflow that followed 4D standards effectively improved repeatability during the stages of processing. Final images around the reservoir showed visible seismic changes along Walkaway VSP orientation post injection during the period between Baseline and Monitor-3. The 4D signal is stronger due to the longer period of injection.

3C VSP processing was performed while taking into consideration Baseline and Monitor-3 NRMS and predictability at each processing step. The customized processing workflow that was developed for Monitor-2 was implemented in the current Monitor-3 processing. The extended Walkaway VSP line provided higher arrival angles to estimate overburden Shale Layer anisotropy parameters in the model which improved the final image. 4D signal was observed on the migrated images at the reservoir level which is consistent with the findings of the rock physics model.

Time-lapse seismic studies are common in clastic reservoirs, yet they are very limited in carbonates. It is believed that this study will add value in understanding the fluid distribution in the reservoir using seismic methods. This will provide better confidence in considering and deploying time-lapse borehole seismic surveys as an initial part of reservoir monitoring activities plan for Enhanced Oil Recovery (EOR) projects. This paper highlights the improvements and optimizations done in acquiring the Walkaway VSP data as well as data processing and interpretation. This workflow can serve as a guide for future time-lapse Walkaway VSP studies.
Breakthrough in Fractured Reservoir Modeling: p-EDFM Approach Resolves Complexities and Accelerates Hydrocarbon Recovery
Authors: Alameri Maitha , Singh M. K. , Tene M. , Rinco S. , Al Kobaisi M. S. , Rat Coriolan , Dias Daniel , Szyndel Matthew , Kada Kloucha C. , Al-Kindi Z. S. , Mustapha H.
Published: November 2024

Fractured reservoirs present unique challenges in the oil and gas sector due to their complex genesis and fluid flow dynamics. Modeling these reservoirs requires overcoming various hurdles, including characterizing complex fracture networks, understanding dual-porosity flow dynamics, and managing scale dependencies. This paper highlights advancements in fractured reservoir modeling technology achieved through a collaborative effort between industry and academia. Our research and technological advancements have culminated in a commercial simulation solution tailored for fractured heterogeneous reservoirs, integrating the projection-based embedded discrete fracture modeling approach (p-EDFM). This method effectively models multiphase fluid flow within highly fractured formations, sidestepping grid complexities and expediting simulation processes. In p-EDFM, fractures are distinctly represented as discrete entities, each with their unique geometry and properties, embedded within a porous matrix with its own characteristics. This breakthrough significantly enhances simulation capabilities for practical applications and establishes a solid foundation for future strides in dynamic, multilevel, multiscale simulations. The new modeling technology facilitates more accurate reservoir characterization, enabling enhanced reservoir management strategies that optimize production rates and maximize hydrocarbon recovery. Additionally, the ability to predict fluid flow dynamics within fractured reservoirs with greater precision empowers operators to mitigate operational risks and minimize environmental impacts, promoting sustainable resource extraction practices. This paper offers novel insights by presenting advanced modeling techniques specifically tailored for fractured reservoirs, including scenarios involving hydraulic fractures where applicable. The performance-to-accuracy ratio achieved by this technology supports effective uncertainty and optimization
Artificial Intelligence for Crew Operations Optimization: A Novel Approach to Passenger Transportation
Authors: Thatcher Jimmy , Amankhan Assilkhan , Eldred Morgan , Rehman Abdul , Vedat Kris
Published: November 2024

This paper presents a case study on enhancing offshore helicopter passenger transportation using artificial intelligence (AI), focusing on refining fleet management, route optimisation, and sustainability. The methodology integrates extensive data analysis, algorithm development, and real-world testing to optimize helicopter schedules and reduce carbon footprints. By correcting fleet status inaccuracies and incorporating variables such as shuttle flights and maintenance schedules, the study develops a dynamic scheduling algorithm that prevents time overlaps and responds efficiently to real-time operational changes. Results indicate that AI-driven solutions can significantly improve operational efficiency—optimising crew assignments and departure intervals, reducing delays by up to 15.70%, and cutting fuel consumption by 8.10%, which also decreases CO2 emissions. This novel approach not only enhances operational efficiency and environmental sustainability but also offers a scalable model for future innovations in offshore transportation logistics.
Operational Insights with Predictive Gamma Analysis to Enhance Drilling Performance
Authors: Davis J. R. , Kolesnik I. , Blackwell B.
Published: November 2024

The drilling process in oil and gas extraction is a multifaceted operation requiring the integration of various systems and technologies. These systems include fluid systems, mechanical rig systems, the drill string, and the bottom hole assembly (BHA), all of which play critical roles in achieving efficient and safe drilling operations. This study focuses on optimizing drilling operations by predicting gamma changes and trends based on drilling parameters measured at the surface, aiming to enhance drilling efficiency, reduce non-productive time (NPT), and minimize the frequency of unplanned trips due to measurement-while-drilling (M/LWD) tool failures.

The study underscores the importance of "knowing the rock" by reducing uncertainty associated with gamma signal lag. This approach empowers drilling teams to manage formation transitions better and improve geosteering, particularly as the industry moves towards longer laterals. In vertical applications, accurate formation transition management and avoidance of unplanned trips due to M/LWD failures are critical for optimizing performance. In lateral applications, predicting gamma trends at the bit enables more precise geosteering and allows drilling to continue despite tool failures.

This paper outlines the method used to generate usable machine learning algorithms for gamma trend prediction using only surface drilling parameters, including: data selection, data preparation, feature engineering, model selection and the challenges experienced. The data preparation process is discussed in detail, including initial data selection, smoothing, filtering, gap handling. Feature engineering involved selecting and transforming relevant drilling parameters, such as weight on bit (WOB), surface rotations per minute (SRPM), differential pressure (DIFF), rate of penetration (ROP), and surface torque (TQ). Pre-processing was conducted to identify steady and non-steady state drilling regimes, with unique models trained for each hole section.

Two types of supervised classification models, Random Forest and XGBoost, were tested for gamma change trend prediction across three different hole sections. The results demonstrated the models' ability to identify and correlate changes in gamma trends with drilling parameters commonly measured on every rig, making the model widely applicable. Discrete models were trained per field and per hole section to account for the differences in drilling techniques across hole sizes and trajectories and proved successful with a low volume of offset data. The model results showed promise for enhancing drilling efficiency and reducing NPT.

In conclusion, this study shows that machine learning techniques can effectively predict changes in gamma trends at the bit by correlating these changes with drilling parameters to optimize drilling operations.
AI-Automated Codification-QC Model for Daily Drilling Reports
Authors: Benzine Abdallah , Tamaazousti Youssef , Vadakkekalam Sudheesh , Balakrishnan Sreejith , Chraibi Imane , Ezzeddine Dhaker , Arnaout Arghad , Khambete Shreepad Purushottam , Bimastianto Paulinus , Muhammad Shahid Duivala , Mughal Idrees Muhamamd , Murad Abdulrahman Abduljalil
Published: November 2024

In the oil and gas industry, Daily Drilling Reports (DDRs) are vital to the well life cycle. Drilling supervisors meticulously record every detail of daily operations, ensuring accurate data is readily accessible for future use. This information is crucial for optimizing operations and future decision-making. However, manually preparing and coding these reports is both time-consuming and costly, introducing the risk of errors that can compromise data quality.

Having accurate data and correct classification of drilling activities are key to making decisions that boost drilling efficiency and cut costs. The precision of DDRs affects how well drilling operations can be analyzed and optimized. But, manual codification by the rig crew often leads to errors, with mistakes in 10% to 20% of entries. These errors stem from the difficulty of categorizing over 400 unique drilling activities, leading to wrong classifications that can disrupt operations and cause expensive errors.

This is where Quality Control (QC) comes in, playing a crucial role in making sure DDRs are accurate. However, QC faces similar challenges, requiring highly experienced engineers to spot and correct errors from the initial coding. These QC engineers need a deep understanding of drilling operations and must be able to pick up on subtle errors in many categories. The complexity and high skill requirements make the QC process as lengthy and prone to errors as the initial coding, highlighting the need for more reliable and efficient methods.
Analysis of Back-Scattered Laser Signal in Oil and Gas Pipelines
Authors: Talele Harshal
Published: November 2024

India boasts an extensive network of over 50,000 kilometers of cross-country pipelines dedicated to transporting oil and gas. These pipelines traverse diverse terrains, rendering them vulnerable to tampering and damage from third-party activities. Despite regular line patrolling by inspectors, incidents of pipeline tapping and damage continue to occur, primarily due to limitations in existing leak detection systems. Current systems, which rely on volume balance methods, are only capable of detecting leaks after they occur. This reactive approach fails to prevent damage or intrusion, leading to significant operational downtime and substantial financial losses from halted refinery operations and disrupted retail outlets. To address these challenges, Bharat Petroleum Co. Ltd has implemented an advanced Optical Fibre-based Pipeline Intrusion Detection System (PIDS). Unlike traditional methods, PIDS offers a proactive solution by utilizing dark fibre for detecting and localizing both unintended damages and deliberate acts of tampering. The system operates on the principles of Coherent Optical Time-Domain Reflectometry (COTDR), where a laser source is injected into the fibre, and backscattered signals are analyzed to identify disturbances along the pipeline. The PIDS system monitors micro-changes in the fibre’s shape caused by various activities, which affect the backscatter signal. This data is processed through sophisticated algorithms and compared against a library of known signatures to detect different types of disturbances, such as manual excavation, agricultural activities, heavy equipment operations, and explosions. The system’s ability to distinguish between these activities is enhanced by a Quick Response Team equipped with vehicles to address potential issues promptly. The implementation of the PIDS system has demonstrated its effectiveness in improving pipeline security and integrity. By enabling early detection and timely intervention, the PIDS system not only minimizes operational downtime and financial losses but also helps mitigate environmental damage. This technology represents a significant advancement in pipeline surveillance and offers valuable insights for other oil and gas industries aiming to enhance their security measures.
End to End Digital Corrosion Management Hub
Authors: Al-Ghazali Eithar , Al-Jabri Nawras S. , Albulushi Yahya Y.
Published: November 2024

The primary objective of the project was to digitalize the Corrosion Management (CM) system within the Asset Performance Management (APM) platform for oil and gas facilities, both offshore and onshore. The aim was to enhance process efficiency by reducing human intervention and error, and to provide a more robust and comprehensive data management system. The scope included the implementation of a new digital CM platform that integrates all recorded CM data, enabling direct and comprehensive analysis through predefined KPIs. This system is intended to monitor and evaluate the performance of corrosion controls continuously.

The new CM solution was implemented on a digital platform that includes handheld devices programmed to interface with the existing computerized maintenance management system (SAP). Technicians use these devices to collect data directly from barcoded equipment at specific TAG locations. This method allows for immediate data entry and upload into the APM software, reducing the need for manual data recording and entry. The platform utilizes a series of check sheet templates that list necessary indicators, ensuring that all relevant data is captured accurately and consistently.

The following are the categories of KPI used to ensure CM performance for Oil and Gas Facilities: Internal Corrosion Management: these KPIs defines the internal corrosion information and ensure reporting on timely mannerExternal Corrosion: these KPIs defines the external corrosion information related to Cathodic Protection and Coating.

The digitalization of the CM system has resulted in significant cost savings, approximately 127K USD annually, by reducing time spent on-site by contractors and staff, and minimizing paperwork. The reduction in manual data entry has also decreased the likelihood of errors compared to traditional paper-based methods. Furthermore, the system has improved the tracking of pending issues and concerns arising from site findings, facilitating more timely and effective responses.

This digital CM solution is unique in its integration of handheld devices with existing maintenance systems, which has not been previously recognized in the market. It has been nationally and internationally acknowledged, receiving appreciation from several clients, and has been recommended for broader implementation. The digital solution not only provides end-to-end digitalization but also innovatively enhances the corrosion management process, making it a pioneering initiative in the field.
Rapid Forecasting of Underground Hydrogen Storage Using Fourier-Integrated Hybrid Neural Framework
Authors: Omeke James , Misra Siddharth , Retnanto Albertus
Published: November 2024

Deep learning can significantly accelerate the simulation of the injection, storage and production processes in an underground hydrogen storage (UHS). By understanding complex system interactions, deep learning offers accelerated simulations, enabling the creation of an fast visualization, forecasting and optimization framework. Our research presents a novel data-driven approach leveraging deep learning to mitigate the computational challenges of high-fidelity underground hydrogen-storage simulations.

In this study, an innovative Fourier-Integrated Hybrid Neural Framework (F-IHNF) is used to create deep-learning-based surrogate models for field-scale hydrogen storage simulation. This framework combines Convolutional LSTM, 3D convolutions, and Fourier Neural Operators (FNO) for precise spatio-temporal analysis, focusing on hydrogen flow dynamics influenced by production and injection cycles. The deep-learning-based accelerated simulation workflow is developed and deployed on Fenton Creek gas reservoir model, segmented into 97×18×35 grid blocks with 61,110 active cells and a grid size of 121ft×136ft×2.8ft.

The newly developed 3D Fourier-Integrated Hybrid Neural Framework (F-IHNF) achieves an impressive 98% accuracy in blind test validation for both pressure and hydrogen saturation forecasting over a period of 2 years involving 3 production-injection cycles. In the data generation phase, 76 simulations of hydrogen storage in various realizations of Fenton Creek geomodel under various engineering parameters were generated over 48 hours, with each 24-month hydrogen-storage simulation averaging 38 minutes. In comparison, the F-IHNF takes 0.5 seconds to forecast the spatiotemporal pressure and saturation evolutions over 24 months. This marks a 5000-time speedup in the forecasting. It took approximately 2 hours to train the F-IHNF model using 60 training samples and 6 validation samples. By finely tuning key hyperparameters—including convolutional LSTM hidden channels, 3D convolutional channels, and the selection of Fourier modes in x, y, and z directions—the precision of F-IHNF was impoved. The use of a weighted mean absolute error for saturation and a normal mean absolute error for pressure resulted in validation MAEs of 0.002 and 0.004, respectively.

This study integrates a Fourier-Integrated Hybrid Neural Framework with deep learning for accelerated simulation of underground hydrogen storage. This approach will support faster analysis, visualization, forecasting, monitoring, and robust optimization, potentially aiding the adoption of underground hydrogen storage in the renewable energy sector for a sustainable future.
Managed Pressure Drilling Technique Commingled High Pore Pressure Section with Depleted Section, Eliminate Drilling Hazard and Pore Pressure Uncertainty Related High-Pressure High-Temperature in West Kuwait Jurassic Deep Wells
Authors: Mokaimi B. S. Al , Alsarhan M. , Mutairi A. Al , Al-Habib H. , Anton J. , Al-Khaldy M. , Selami B. , Benyounces H. , Alqabandi R. M. , Marin G.
Published: November 2024

The main goal was to successfully drill a re-entry well in the Rahiyah Field, West Kuwait, overcoming the challenge of commingle drilling from the Najmah to Middle Marrat formations characterized by High-pressure High-Temperature (HPHT) conditions and significant pressure uncertainty.

A high-level Managed Pressure Drilling (MPD) strategy was developed, involving the use of a 15.2 ppg mud weight with an Equivalent Circulating Density (ECD) of 16.9 ppg. The plan included performing Dynamic Pore Pressure Tests and MPD Build Up Pressure Tests at the bottom of the Dharuma Formation to accurately determine the pore pressure across transitional zones. Adjustments to mud weight and ECD were made based on real-time data, facilitating adaptation to varying well conditions.

The application of MPD techniques allowed for efficient and safe drilling through a highly uncertain pressure window, reducing the drilling time of commingled sections to 10 days, compared to over 30 days typically required for re-entry wells. The conventional approach would have necessitated a higher mud weight of 16.9 ppg, potentially causing a cycle of fluid losses and differential sticking. The oil-based mud (OBM) for the well’s final total depth (TD) was modified to a lighter density of 12.6 ppg with an ECD of 14.0 ppg, mitigating common issues in HPHT environments. This resulted in significant time savings and reduced non-productive time (NPT), demonstrating substantial improvements over traditional methods.

This case study demonstrates the effectiveness of combining MPD with real-time pressure assessments to manage significant pressure variations in deep well environments. The learnings from this pilot project are crucial for refining cost-effective field development strategies and could significantly influence well trajectory planning, completion designs, and recovery optimization in similarly challenging geological settings.
The Outstanding Geological and Stratigraphic Features Revealed by Abu Dhabi Mega Seismic
Authors: Elila A. , Al Hammadi M. , Xie A. , Al Hammami S.
Published: November 2024

The paper aims to showcase the significant role of mega seismic survey in identifying geological and stratigraphic features that were previously unclear in legacy seismic data, particularly in deeper sections. This has been achieved through the acquisition and processing of seismic data in such a way to produce a sharp image of the geology with minimal noise. The techniques employed include but not limited to broadband, high fold, long offset, full azimuth seismic data acquisition, up- down deconvolution, and FWI & RTM migration, which have resulted in detailed and well-imaged geological and stratigraphic features that would not have been discernible without the application of these advanced seismic data acquisition and processing techniques
Measuring Variations in Rock Mechanical Properties Due to CO2 Injection: Application of Nano-Indentation
Authors: Dontoh William Holdbrook , Mews Kim , Ghanbarian Behzad , Alhajeri Mubarak , Barati Reza
Published: November 2024

Injecting CO2 into geological formations has become an important process for carbon sequestration to reduce atmospheric CO2 levels and mitigate climate change. Therefore, understanding the impact of CO2 injection on rock mechanical properties is essential for assessing the integrity and safety of storage sites. This study employs nanoindentation to measure variations in rock mechanical properties caused by CO2 injection. Nanoindentation provides localized measurements of hardness and elastic modulus. Results indicate significant alterations of more than 95% reduction in Young's modulus of the carbonate rock samples post-CO2 injection, with implications for the long-term stability of sequestration sites. This research contributes to the development of more accurate models for predicting the mechanical performance of CO2-injected carbonate rocks, ultimately enhancing the safety and efficacy of carbon sequestration and enhanced oil recovery using CO2 efforts.
Case Study of the Pioneering Coring Preservation and Management of the First Underground Oil Storage in the Middle East Region
Authors: Osama Mohamed , Salem Gamal , Sumaida Ali Bin , Shamlan Abdulla Bin , Almazrouei Saeed , Al Marzooqi O. , Draz Alauddin Abou , Alajami Abdulaziz , AlSabi Haya , Siddiqui Faisal , Al Shehhi Mouza , El Yossef Bassem S. , Ahmed Mohamed , Abouseada Mahmoud
Published: November 2024

Underground Gas Storage (UGS) is considered a strategic method to balance the supply-demand chain of the energy required in a more economical and feasible way to save some of the storage challenges. The caverns were solution mined into subsurface salt domes, is the focus within the oil & gas industry over the past years. In the absence of caverns, in previous storage studies, oil was initially thought to be stored in porous sedimentary rock formations.

Oil stored underground in geological formations is commonly kept in salt caverns. Salt caverns are engineered from naturally occurring salt domes and due to the plastic nature of the salt, it makes it both efficient & beneficial for the storage of crude oil due to its healing nature of any fractures rapidly due to the pressure nature 2000-4000 feet underground that may occur within the salt. Wells provide the mechanism for the transport of fluids (oil and brine) into and out of the caverns. The wells are constructed in such a way as to provide critical isolation of cavern fluids from the surface environment and groundwater. Studies resulted in proven results for the Salt cavern storage to be a safe, reliable, sustainable, and cost-effective method for storing hydrocarbons, including crude oil, Strategic Petroleum Reserve (SPR) oil, and other refined products.

One of the first steps in this project, requires many sets of lithological data analysis and experimenting and that is the focus of this paper. Extensive core acquisition program was required from well's surface depth till TD, in order to have a full overview/analysis done on all sort of lithological changes across the well for better understanding in executing the salt caverns project. This paper focuses mainly on the coring program for handling core samples from the acquisition process till the preservation and handling phase. This also includes all application challenges from planning, execution to the lessons learned and results/conclusion along with the coring new record runs achieved for the first time setting new possibilities in performance and efficiency delivered with 100% recovery rates.
Fueling Sustainability: End-To-End Digital Oil Field Integrating Production Growth, GHG and Economic Management
Authors: AL Jadidi I. , AL-Saqri K. A. , Al Busaidi H. M. , Al-Mujaini A. S. , Al Ghafri R. S. , Alsharji H. , Al-Ghadani A.
Published: November 2024

The project objective was to build a customized field performance dashboard for enhanced opportunity management and visualization of prioritized surface and subsurface system optimizations. Moreover, it is part of global PDO vision towards digitalization. The project covers production, injection and facility systems using Integrated Production System Management, IPSM, tools which is connected to Digital Oil Field, DOF, Dashboard.

The Automation of Well Model Creation has significantly added value in reducing the total process time from days or weeks into minutes (The traditional average time per well model was around 4 hrs). this Portal has expedited the traditional labor-intensive process and leverage team productivity, while minimizing human-induced errors. The massive cycle time reduction unlocks the opportunity to keep the evergreen sustainable well model status and enables the team to spend more time in identifying the well optimization opportunities early in the game.

DOF as a tool was built to fuel the sustainability of the IPSM maintenance and value realization which is considered as one of the major challenges in any Well, Reservoir and Facility Management, WRFM, business. The above concept of End-to-end WRFM optimization is applicable to most of the water flooded Oil fields with ESP producers.

Significant Economic value has been realized from DOF through real time production and injection monitoring and optimization identification, well test validation and hidden deferment evaluation.

Taking a look to the global oil and gas industry perspectives; DOF adoption is a key lever for Cost competitiveness, Sustainable Production Growth and Gap-to-Potential optimization. An innovative practice to incorporate well operating economics and power consumption with global optimization to align with decarbonization targets. OPEX and Energy consumption analysis was an innovative addition to DOF to minimize GHG emissions and improve cost competitiveness.
Unlocking the Potential of a Giant Carbonate Reservoir: Optimizing Oil Recovery in Tight Zones Following a Long Period of Gas Injection Development
Authors: Abdelaty H. H. , Shbair A. , Alshehhi F. M. , Gutierrez R. R. , Almamari R. H.
Published: November 2024

Recurring evaluation of the selective completion and development strategy of individual reservoirs is crucial to ensure optimal performance. This paper presents a new approach for optimizing the injection scheme in highly communicated reservoirs. After a long period of gas injection in the subject reservoir, gas percolation to the overlying reservoir becomes critical. This paper aims to propose a plan that can enhance the recovery of the subject reservoir without compromising other reservoirs’ performance.

A full-field reservoir simulation model, in integration with surveillance data, including a tracer study were used to investigate various development scenarios, including additional wells, artificial lift need, voidage replacement ratio, balance between peripheral and pattern water injection, and the optimum target injection rates. After each scenario, it was observed that the predominant heterogeneities caused a large amount of oil to be left behind. Therefore, this paper also demonstrates a method for locating and quantifying the remaining oil and determining the best techniques for its recovery. The optimized scenario resulted in an extended plateau and an increased recovery.

The results demonstrated the benefits of switching from gas injection to water injection in the parts of the reservoir where water injection was feasible. The extreme north of the reservoir where water can’t be injected without fracturing, has insignificant remaining oil after long time of gas injection. The gas injectors in this part of the reservoir are sidetracked within the reservoir and switched to water injectors. These actions reduced the gas percolation to the upper reservoir, increased the ultimate recovery, and enhanced the economics significantly due to the lower operating cost. The new development plan of the subject reservoir showed the importance of thoroughly evaluating and integrating all the available data and connecting these data with the reservoir geology to better position the new wells. The updated development plan led to extension of the production plateau resulting in additional recovery and improved economics.

This paper highlights the importance of optimizing the injection scheme for the target and neighboring reservoirs. It highlights that relying solely on common development options does not recover the remaining oil effectively. To enhance recovery, the paper presents a method for quantifying and targeting the remaining oil to select the most suitable recovery technique.
Overcoming Challenges in Congested Environment to Successfully Drill CO2 Injection Project Which Holds Immense Value in Terms of Sustainability and Reducing CO2 Emissions in ADNOC Onshore.
Authors: Kodiah B. , Bethancourt R. , Al-Reaymi M. , Al-Jabery R. , Al-Wahedi K. , Nazarov T. , Khan F.
Published: November 2024

The SWAG (Simultaneous Water and Gas) injection project represents a significant milestone in enhancing oil recovery methods within the region. This project, the first of its kind in our area, faced numerous challenges, primarily concerning the selection of suitable drilling locations. The densities of managing both surface locations and subsurface targets added layers of complexity to usual drilling demanding operations.

The drilling targets were confined to a specific reservoir area, imposing precise adherence to location constraints. This limitation established a considerable challenge as we attempted to find a suitable surface location amid a congested field in a specific location surrounded by multiple facilities and roads. The congestion in the area not only complicated the logistical planning but also threatened to delay the project's timeline significantly.

Among the critical challenges were the difficulties in finding a surface location in a highly congested area, planning the well trajectory to ensure precise targeting of subsurface objectives, and mitigating collision risks with existing wells and the project wells. Additionally, the operation required drilling through multiple reservoirs, each characterized by significant pressure variations, which added to the complexity and risk of the drilling process.

Despite these barriers, Drilling, Asset development and Production teams collaborated closely to devise an innovative solution. By slightly shifting the proposed surface locations and repositioned to be in a straight line at a new PAD location in alignment with the subsurface targets, we were able to circumvent the congestion issues. This strategic adjustment not only facilitated smoother operations but also resulted in significant time and cost savings during the location preparation phase and during production facilities preparation prior drilling the wells.

This paper details the challenges encountered during the SWAG project's initial phase, the solutions implemented, and the lessons learned up to the current stage of the project. Our experience underscores the importance of flexibility and innovation in overcoming logistical barriers in complex drilling projects. Through these efforts, we aim to contribute valuable insights to the industry and pave the way for future projects in similarly constrained environments.
Experimental Investigation of Salinity and Pressure Impact on CO2 Solubility in Saline Aquifers
Authors: Elmasry Youssef , Enab Khaled , Addo-Mensah Alfred
Published: November 2024

Addressing global climate change necessitates innovative solutions for carbon capture and storage (CCS). With their vast capacities, saline aquifers emerge as promising repositories for CO2 sequestration. While solubility is the primary trapping mechanism for CO2 in saline aquifers, a significant knowledge gap exists regarding the role of salinity level and operation pressure on the CO2 solubility in saline. This study delves into the experimental investigation of CO2 solubility in different saline aquifers, focusing on phase behavior analysis through the use of a Pressure-Volume-Temperature (PVT) cell. The research aims to enhance our understanding of the fundamental interactions between CO2 and brine under reservoir conditions, critical for optimizing CCS strategies. Experiments were conducted to observe CO2 solubility in five different brines with different salinity levels at various pressures. The experiments were designed to measure the equilibrium phase behavior of the CO2-brine system, providing valuable data on CO2 dissolution rates and phase transitions under a range of pressure settings. The experimental data revealed that pressure and salinity significantly influence CO2 solubility in saline aquifers. Higher pressures were found to increase CO2 solubility, while the effect of salinity presented a more complex interaction; lower brine salinity showed higher storage and CO2 dissolution. These findings contribute to a deeper understanding of the thermodynamic principles governing CO2 sequestration in saline aquifers and highlight the importance of tailoring CCS operations to specific reservoir conditions.

sIn conclusion, the results of this experimental investigation illuminate the critical role of phase behavior analysis in understanding CO2 solubility in saline aquifers, marking a significant step forward in CCS technology. Integrating the presented empirical data with analytical modeling is the way to develop a new pathway for enhancing the efficiency and reliability of CO2 storage in saline formations. The results of this research efforts contribute to the broader effort of mitigating atmospheric CO2 levels and combating climate change. This model serves as a powerful tool for CCS project planning and optimization, enabling more accurate estimations of CO2 storage capacities in saline aquifers. The implications of this research extend beyond theoretical advancements, providing practical guidelines for the design and implementation of effective and safe CO2 sequestration projects.
Design and Installation of an On-Demand Activated Electronic Liner Shoe Mitigates Risk of Differential Sticking and Eliminates Intervention Cost
Authors: Beaman D. A. , Al Ali O. J. , Abdalla H. M. , Abdelghany M. M. , Young D. A.
Published: November 2024

This paper presents a case study of the first installation of an on-demand activated Remote Actuated Shoe (RAS) in offshore extended-reach wells. The Middle East operator faced challenges related to potential differential sticking while running lower completions in high overbalance conditions.

To mitigate this risk, the liners were equipped with isolation-valve Inflow Control Devices (IVICD) and a system at the toe of the liner to allow circulation from the shoe. However, conventional ball drop-activated shoe valves proved unreliable and time-consuming, often leading to expensive interventions to close the liner shoe. In collaboration with the operator, the original equipment manufacturer (OEM) designed a fit-for-purpose RAS tailored to offshore applications. The RAS was programmed to close after measuring 400 psi above hydrostatic pressure for 45 minutes, providing an on-demand solution for immediate closing of the liner shoe after reaching total depth (TD). A ported bullnose with choke functionality was also designed to create the pressure increase during circulation to signal the RAS to close once at depth.

Upon reaching TD with the lower completions, the wells were circulated for the prescribed 45 minutes before seeing the indication that the shoe had shut, and the completion was successfully set as per plans. The successful installation of the on-demand RAS resulted in significant cost savings, with $1 million saved in potential intervention costs and a reduction of 120 metric tonnes of CO2 emissions per well. Two offshore wells have been completed successfully so far using the on-demand RAS, leading to its adoption as the standard liner shoe for the operator's offshore extended-reach wells in these fields.

This case study demonstrates the effectiveness of the on-demand RAS in mitigating risks associated with high overbalance conditions, differential sticking, and operational challenges during the installation of lower completions in offshore extended-reach wells. The findings highlight the potential for significant cost savings and environmental benefits through the adoption of innovative intervention less technology in oil and gas operations.
Carbon Capture Options For Gas Processing Facilities
Authors: Kannan Srihari , Conradus Isabel
Published: November 2024

For operators of gas processing facilities seeking to decarbonise their operations through carbon capture, one significant challenge stands out: identifying the optimal point within the processing line-up for recovering a high-purity CO2 stream suitable for sequestration. By conducting a comprehensive techno-economic assessment of principal capture points within the gas processing line-up, this paper aims to provide valuable insights to address this specific challenge.

In this study, we will evaluate capturing CO2 (pre or post combustion) from various points within a standard natural gas treating line-up consisting of an acid gas removal unit (AGRU), acid gas enrichment unit (AGEU), sulphur recovery unit (SRU), tail gas treating unit (TGTU), and incinerator.

Real-world scenarios encountered by Shell Catalysts & Technologies’ customers inform our assessment, drawing upon simulations and designs developed by our team. For instance, recent projects like the one at Abu Dhabi National Oil Company, capturing CO2 post combustion from the TGTU, contribute valuable insights to our analysis.

The paper will conclude that the optimal location varies according to a wide range of factors, including the composition of the feed gas, particularly the levels of sulphur, and plant-specific requirements such as sulphur recovery efficiency and environmental regulations.

Crucially, we will also provide insights into the circumstances favouring each capture point. For example, the AGRU is advantaged for high-pressure CO2 capture, contingent upon very low sulphur content in the feed gas. However, there are circumstances in which the AGEU, with the right solvent, could be more effective, especially as it could achieve the twin purpose of preparing acid gas that is suitable for the SRU and generating a CO2 stream fit for sequestration. Such insights are crucial for operators seeking to implement an effective carbon capture project.

Carbon capture at gas processing facilities is relatively new, and uncertainty prevails in pinpointing the optimal location for CO2 capture. By tackling this challenge, this paper offers valuable, practical guidance for operators navigating the complexities of decarbonising gas processing facilities. It contributes to the evolving understanding of carbon capture technologies, facilitating more informed decision-making within the energy industry.
Leveraging LWD Ultrasonic Imaging for Enhanced Fracture Identification in Water-Injection Wells
Authors: Al Saidi Hamdan , Al Harth Al Maha , Das Anindya , Al Shuali Salim , Al Salmi Issa , Al Sawafi Samya , Al Muharabi Mubarak , Taher Ahmed
Published: November 2024

Carbonate formations are known to be highly fractured. Water injection plays an important role in enhancing oil recovery, and accurate identification and characterization of fractures in the reservoir are crucial for optimizing injection strategies and ensuring efficient fluid displacement. This study investigates the application of logging-while-drilling (LWD) ultrasonic imaging technology as a tool for fracture detection and characterization in water-injection wells.

Carbonate reservoirs are usually characterized by the presence of natural fractures. High-resolution ultrasonic imaging sensors acquire amplitude and travel-time images for identifying open fractures and measuring hole size. The integration of formation evaluation data and high-resolution images provides important information for reservoir characterization.

The data in this study was acquired across a reservoir section for optimizing well injectivity. The study presents results from field trials where LWD ultrasonic imaging was employed for fracture identification in water-injection wells for the first time in the Upper Shuaiba formation, with no other water-injection wells nearby. The analysis focuses on the tool's ability to detect fractures, including their orientation, size, and distribution.

Lost-circulation intervals associated with open fractures were resolved by the high-resolution image. The upper section of the drilled interval appeared to be highly fractured with some cemented fractures. Five faults were identified, most of them associated with multiple fractures and loss of circulation. The shallow resistivity log across the highly fractured zone showed clear variations due to the presence of fractures. The general fracture direction was NW-SE with some less frequent fractures with different fracture orientations aligned in the NE-SW direction. Bed dips picked from the borehole image showed a consistent SE dip direction with average dip of 7 degrees.

The deployment of the ultrasonic imaging sensor in an injector provided important information for understanding fractures connectivity and its influence on injectivity. This knowledge can be used to improve reservoir performance.