Halliburton (United Kingdom)

Abstract The Oilfield A is a highly complex fault-block reservoir segmented by 80 faults into over 40 small blocks, each averaging only 0.3 km2 in area. This structural complexity results in low recovery efficiency, with remaining oil primarily concentrated in the peripheral fault blocks. Certain blocks exhibit steep dips of up to 20° with significant variations, presenting substantial challenges for horizontal well trajectory design and reservoir exposure. To address these challenges, a resistivity reservoir mapping tool was deployed during horizontal drilling to provide real-time structural and stratigraphic insights, optimizing well placement. Steeply dipping formations introduce complex current pathways, significantly impairing resistivity measurement accuracy and imaging resolution. To mitigate these challenges, an enhanced resistivity reservoir mapping tool with four operational frequencies was employed. Geological models were constructed using offset well resistivity data, and frequency responses in steeply dipping formations were simulated to identify the optimal frequency combination for improved reservoir mapping resolution. Furthermore, the conventional inversion algorithm was improved to accommodate larger dip angles, increasing tool adaptability. Near-bit logging data were also integrated to identify abrupt local stratigraphic changes. The implementation demonstrated that the optimized frequency combination achieved excellent compatibility with the formation. The improved resistivity inversion algorithm effectively mapped structural variations, identifying dip changes from 15° to 21° and capturing a progressive thinning of the formation from 13 meters to a pinch-out. Reservoir exposure reached 85%, and production exceeded expectations by 50%. This successful application provides critical insights into horizontal well development in steeply dipping and complex reservoirs, offering significant potential for broader field applications.

Abstract Recently, there has been a growing focus on understanding material behaviors to improve product designs in the oil and gas (O&G) industry. This paper aims to apply fracture mechanics principles to predict the stress and strain state of rubber when feeding lines through splice-less swellable packers. Specifically, various rubber elastomer shapes are examined through Finite Element Analysis (FEA) in ABAQUS/Explicit, guided by experimental data. The fracture damage mechanism of rubber is more complex compared to metallic parts, and it is crucial for ensuring product reliability. In cased or open-hole environments, swellable systems with cable feedthroughs are utilized to achieve zonal isolation of producing zones during downhole operations. A dedicated tool has been developed to facilitate cable installation during the feedthrough process. To have a better understanding of hyper-elastic behavior in rubbers at large deformations and identify optimal geometrical designs, FEA is conducted in ABAQUS/Explicit, coupled with a user subroutine (VUSDFLD). Test results are used to calibrate the material properties, enabling a comprehensive representation of the material behavior under damage conditions. The experimental model is replicated by a finite element model based on the comparison of measured and calculated forces acting onto the rubbers. Similar deformation patterns are observed. In the numerical model, the initial development is based on maximum principal strain-based crack initiation, with element removal utilized to approximate the damage initiation and evolution. With such a calibrated numerical model, four different geometries are examined: circular, square, trapezoidal, and winged shapes. The optimal design is determined based on achieving the lowest load to stroke the same displacement while minimizing the volume of rubber with higher strain state. It's found that the optimal shape is the winged shape, significantly reducing peak principal strain around the hole boundary compared to typical circular profiles. In summary, fracture mechanics principles are studied and applied in the numerical analysis to predict the stress and strain states of rubbers and provide guidelines in the tool designs in cable feedthrough installations. This approach ensures enhanced reliability of cable systems, crucial for risk reduction during completion system installations.

Abstract This paper presents a comprehensive experimental and analytical study on core flow efficiency (CFE) and single-shot perforation skin in sandstone cores, with a focus on deriving crushed-zone permeability and thickness. A novel experimental method for determining the theoretical ideal tunnel rate index (RIth) is introduced and benchmarked against the two established methods outlined in API RP 19B (2021): analytical approximation and numerical modeling. The new method eliminates the need for prior knowledge of the core's virgin permeability and accounts for core heterogeneity, offering a more physically representative assessment of perforation performance. The study incorporates three-dimensional tensor characterization of both permeability and inertial resistivity, providing a detailed understanding of anisotropic flow behavior in sedimentary rock. Laboratory tests were conducted under realistic downhole conditions using San Saba sandstone, with post-shot flow testing and CT imaging used to quantify effective flowing perforation tunnel length and geometry. Key findings include: The experimental RIth method produced results consistent with established methods in homogeneous cores, but revealed significant discrepancies in heterogeneous samples, highlighting the limitations of conventional assumptions.Negative skin values observed in some tests using established methods were resolved through the experimental approach, which yielded physically consistent results without post hoc adjustments.A two-by-two matrix of inflow modeling parameters was developed based on core permeability and peak dynamic underbalance (DUB), enabling practical application in well performance simulations. This work advances the state of perforation analysis by integrating rigorous experimental design, advanced flow modeling, and full-tensor core characterization. It provides a robust framework for evaluating perforation damage and cleanup, with direct implications for optimizing well completions and improving reservoir inflow performance.

Abstract A calibrated, up-to-date model provides valuable insights into network bottlenecks and enables optimization of chokes and artificial lift settings to enhance overall production efficiency. This paper presents the development of a digital twin for a giant onshore oil asset, featuring a surface network model that updates daily with real-time well and network data. The model captures new well connections, status changes, and re-routing, and automatically calibrates choke settings and surface network parameters. Surface network data is extracted daily from KOC's corporate databases and loaded into the KwIDF database using ETL (Extract, Transform, Load) processes, ensuring compatibility with the simulation environment. Real-time data from wells, manifolds, and facilities is sourced from KOC's live data systems. The foundational surface network structure—comprising pipeline lengths and diameters—is manually derived from GIS maps and stored in a central repository. An integrated tool automates model building and calibration through several dedicated workflows. The AIVGAC (Automatic IPR/VLP Generation and Conversion) workflow transforms calibrated well models into IPR/VLP curves. ANMB (Automatic Network Model Builder) updates the surface network and integrates real-time data. AIVWMV validates well model quality, while ACC (Automatic Choke Calibration) and ANMC (Automatic Network Model Calibration) fine-tune choke settings and flowline connections, respectively. The HR (Hourly Run) workflow executes the model hourly, generating virtual flow rates across the network. Finally, ACEO (Automatic Choke & ESP Optimization) recommends optimal choke and artificial lift parameters. This fully automated system ensures the digital twin remains current, accurate, and capable of supporting real-time operational decisions. Results are presented per gathering center (GC) on a dedicated GC Summary page, which displays model outputs alongside input data quality indicators. The Network Heat Map visualizes active pipeline connections and provides key parameters such as phase flow rates, pipeline specifications, and real-time measurements. Alarms and alerts are automatically generated for conditions like high pressure loss index, header switching (LP to HP and vice versa), low or no flow, and discrepancies between real-time and model data. The ACEO dashboard lists wells with their recommended optimal choke settings and ESP frequencies, enabling targeted operational adjustments. Additionally, the Network KPI page evaluates the quality of real-time and well test data used in the models, ensuring transparency and reliability in decision-making. Together, these interfaces provide a comprehensive, real-time view of network performance and optimization opportunities. This paper highlights the value of a fully automated digital twin that updates, calibrates, and delivers daily production optimization recommendations. By integrating real-time data and advanced workflows, the system enables continuous, data-driven decision-making to enhance operational efficiency and maximize asset performance.

Abstract Hydrocarbon exploration and development within the State of Kuwait have entered a technologically advanced phase characterized by integration, digitalization, and predictive modeling. As the Kuwait Oil Company (KOC) pursues its 2040 strategic vision to expand production capacity while maintaining operational safety and sustainability, geomechanics has become a central discipline linking geology, drilling, and reservoir engineering. Among the Jurassic stratigraphic intervals, the Najmah and Sargelu formations represent key exploration and development targets due to their dual role as prolific source rocks and potential unconventional reservoirs. The mechanical characterization of these formations is complicated by lithological heterogeneity, high organic content, and complex stress regimes arising from both local and regional tectonic influences. This study develops a comprehensive workflow for constructing a full-field three-dimensional (3D) Mechanical Earth Model (MEM) in the Burgan Field, Southern Kuwait. The workflow transitions from multi-1D well-based geomechanical models to a predictive 3D representation integrating petrophysical logs, laboratory rock mechanics testing, seismic interpretation, and structural geology. Overburden stress was computed using density-derived vertical stress gradients; pore pressure was estimated via the Eaton method and calibrated against drilling data. Elastic and strength parameters were obtained from laboratory tests and empirical correlations, propagated spatially through geostatistical kriging constrained by seismic facies. The 3D MEM enables visualization and quantification of the stress regime, pore pressure distribution, and rock mechanical heterogeneity across the field. The model reveals a predominantly normal to strike-slip stress regime, with maximum horizontal stress trending northeast–southwest in alignment with regional tectonic compression from the Zagros fold-thrust belt. The Najmah Kerogen interval, characterized by low stiffness and high organic content, emerges as the mechanically weakest unit controlling wellbore instability. Mud-weight window analysis identifies optimum drilling weights between 10.2 and 12.0 ppg for minimizing collapse and fracture risk. The developed 3D MEM represents a significant step toward field-scale predictive geomechanical modeling in Kuwait. It supports well planning, borehole stability assessment, and completion optimization, while establishing a methodological foundation for basin-scale MEM development. Future extensions integrating seismic inversion and forward stratigraphic modeling will enhance the model's predictive capacity and facilitate a holistic understanding of stress evolution across the country's Jurassic reservoirs.

Abstract This paper presents the effective deployment of high-resolution logging-while-drilling (LWD) acoustic imaging in a frontier exploration well drilled under extreme conditions, including an equivalent circulating density (ECD) of 20.6 ppg, static mud weight of 19.3 ppg, and temperatures peaking at 293°F. The objective includes assessing the tool's capability to detect borehole conditions and geological structures, particularly fractures, and to align these observations with core data and production outcomes. The project involved drilling a 6-in. vertical reservoir interval using a rotary bottomhole assembly (BHA) outfitted with gamma ray, resistivity, sonic, and ultrasonic imaging tools to capture conventional and high-resolution acoustic image data. Despite severe drilling parameters, including ECD values surpassing 20 ppg, the imaging tool recorded comprehensive and sharp visuals. Sophisticated processing methods were used to analyze the acoustic imagery, which was then compared against core data and production results to confirm fracture interpretation. The LWD imaging system produced clear, high-resolution visuals that identified numerous fractures within the reservoir and provided borehole breakout data. These fractures were accurately matched with findings from core sample analysis and Coriolis mud logging at equivalent depths. These links, combined with production figures, affirmed fracture presence, substantiating the imaging tool's output. Breakout data also enhanced understanding of wellbore stability and mud weight optimization. In similar settings, the LWD images were evaluated against wireline images, supporting the LWD data's quality. This study emphasizes the benefit of acquiring measurements during drilling, before major borehole wall degradation. Its success under extreme conditions demonstrates the tool's dependability and precision, underscoring its relevance for future exploratory drilling. This paper records the first global success in applying high-resolution LWD acoustic imaging in environments with such elevated mud density and temperature. The exceptional image clarity, along with confirmation from core and production analyses, offers fresh understanding of fracture detection and formation analysis under harsh drilling conditions, significantly enhancing knowledge of the tool's performance and trustworthiness in previously untested scenarios.

Abstract Onshore field of South Sumatra basin are known as one of the largest oil petroleum systems in Indonesia. Its production rates are considerably high and healthy as there are multiple target layers of sandstone reservoir with sustainable pressure (Galih, et al.2023). This natural ease had levelled up the confidence to do extraction with factory wells design, means applying similarity of drilling operations (such as trajectories profile and BHA configuration) for several areas in the field. The significant amount of time in preparation was reduced with this method. The next level of time saving comes from maximizing the drilling operations in each well. The case study in this paper will elaborate the initial implementation of drilling technology known as intelligent rotary-steerable-system (RSS) push-the-bit to improve each well delivery time. Two types of wells, which represent the most common design of trajectory in this subject field, were selected to implement this novel technology. On a J-Type well with target inclination of ~ 22 deg, RSS capabilities are reviewed in the 12.25in hole section by gauging the performance in maintaining tangent interval of ~770 m. In a S-Type well with maximum inclination of ~18 deg inclination, RSS was evaluated in the 8.5in hole section on holding a verticality until the end of well for ~785 m. Both cases were having a comprehensive logging-while-drilling (LWD) suite consisting of gamma ray, resistivity, density, neutron porosity, pressure-while-drilling, and vibration mitigation tool. In addition, this technology is equipped with an automation platform which enables autosteer services to achieve precise steering with a reduced tortuosity borehole, while simultaneously increasing the rate-of-penetration (ROP). Offset wells analysis of each field had helped to form optimized configuration for the RSS. Identification of formation hardness, lithology lamination, loss, washout and tight hole hazard zones, reactive shales, and hard stringers were all considered in the optimization of RSS hydraulics design. Overcoming respective challenges, Target Well-1 has successfully achieved a significant ROP of ~65 m/hr with precise placement of 0.15 m center-to-center to plan and average dog-leg-severity (DLS) at ~0.5 deg/30m in the 12.25in hole. Laminated formation with massive change in strength properties, was a major challenge in this Field-G that may cause steering drift. Performance of automation platform plays a prominent role in achieving quick and adaptive control. Intelligent RSS ability of applying automated trajectory control, coupled with active machine learning algorithm had managed to secure precise placement in this well. In Field-B, Target Well-2 successfully achieved up to ~80 m/hr with 1.55 m center-to-center to plan and average of DLS 0.2 deg/30m in 8.5in hole. Excessive torsional vibration is a repetitive obstacle in this Field-B environment and has reduced the BHA outcome in several wells. The stability and consistency of RSS performance throughout this run had enabled a good quality borehole. intelligent RSS and the autonomous drilling platform predicting the optimum commands to create a smooth wellbore. A new benchmark was set in this entire factory wells project. These first runs in each field have proven the capabilities to push time and cost savings by applying novel technology in drilling operations. The case studies show the proven RSS can produce benefits of up to 3 times higher delivery time compared to the surrounding offset wells that utilize conventional mud displacement motor. Future applications towards the entire campaign may significantly be a game-changer in onshore drilling operations.

Abstract Drilling anomalies continue to occur across well operations despite the availability of extensive relevant data. This gap between available knowledge and execution outcomes highlights the limitations of traditional planning approaches and the difficulty in effectively leveraging historical data in real time decision-making. The integration between collaborative multidisciplinary planning software and a knowledge management system presents a breakthrough in planning wells. This case study explores benefits of the integrated environment, focusing on the enhancement operational efficiency. The integration between the collaborative well planning software and the Knowledge Management (KM) system provides a seamless digital connection between the multidiscipline engineering departments and the rig sites. This allows the asset teams to better visualize and manage data improving operational decisions in real time. The integrated environment uses graphic symbols to represent different downhole incidents and display them in 3D subsurface models and wellbore views. The integrated software enables a diagnostic review of stored data, displaying incidents and their exact coordinates on the 3D subsurface model. This allows studying the relationship between incidents, their frequency, and location. The Knowledge Management workflow through the integrated software generates high quality drilling and completion historical datasets and lessons learned which are utilized in future projects to optimize well plans and consequently improve drilling performance. The integrated software helps diagnose planned and unplanned activities, non-productive durations, and other key depth-based data. Comprehensive 3D visualization helps study how drilling incidents relate to known faults and surface grids, and where certain incidents tend to occur. This visualized correlation helps improve the decision-making process for the multidisciplinary teams. The integrated software also serves as a central hub for drilling-operations knowledge management. This enables reviewing potential incidents, preparing contingency plans, and capturing lessons learned. Collaboration between drilling, geoscience, petrophysical, and assets teams is significantly optimized through the collaborative environment presented by the integrated software. Real time data feeding into the integrated software coupled with the 3D digital visualization permits a wholistic management of the operations across the field, resulting in the following benefits: Stuck pipe depths analysisMud loss identificationReduction of geo-mechanical uncertaintySophisticated sidetrack kick-off points analysisTrajectory complexity analysisReaming events analysisReduction of non-productive timeImproved real time interventions The successful coupling between a collaborative multidisciplinary planning software and a knowledge management system is newly trialed at the onshore fields of Abu Dhabi. Testing the true efficiency of the studied collaborative integrated digital environment on a wide range of multidisciplinary data and operations provides novel results. This unlocks hidden knowledge that is efficiently utilized to optimize well planning, operations, and associated costs.

Abstract This paper outlines the development of a gas field in a mature carbonate reservoir via an onshore Extended Reach Drilling (ERD) well in Abu Dhabi, featuring a 24,000-foot lateral section. The operator aimed to achieve a drilling rate of 1 mile per day. However, both the landing and lateral sections presented significant drilling and geological challenges, including subsurface uncertainty, rig limitations, high downhole temperatures, and Effective Circulating Density (ECD) management. In addition, maintaining 100% reservoir contact required frequent well path adjustments via manual geosteering, introducing performance variability and human error. These challenges constrained the rate of penetration (ROP) and increased overall well costs. This paper presents a customized drilling and subsurface solution combined with a downhole drilling automation system that enabled 100% reservoir contact and saved 4.6 drilling days. A new Intelligent Rotary Steerable System (RSS) was deployed in combination with an Ultra High Torque Motor to maintain consistent weight on bit (WOB) and differential pressure (>500 PSI while drilling) along with compatible bit to achieve target ROP. Deep Reservoir Mapping tools were critical in navigating the thin carbonate reservoir, enabling real-time identification of formation dip changes and reservoir boundaries above and below the wellbore, contributing to higher ROP. Autonomous downhole directional drilling tools allowed continuous well-path adjustments, enhancing placement precision within the reservoir. Integration with automated geosteering software reduced decision-making cycle time from ∼15 minutes to <5 minutes. The closed-loop automation also minimized RSS setting changes, promoting smoother wellbores and facilitating efficient deployment of the production Bottom Hole Assembly (BHA), while reducing invisible lost time. Vibration mitigation was achieved through the combined use of Motorized RSS and Anti-Stick Slip tools. The well reached total depth (TD) at 34,127 feet Measured Depth (MD) successfully with 23,095 feet of 8½" lateral section drilled, and 100% reservoir contact achieved. A record onshore daily footage of 4,076 feet was attained in the UAE. This marked the global debut of the new 6¾" Motorized RSS. Integration of the autonomous downhole directional drilling system with the Motorized RSS and Deep Reservoir Mapping enabled precise control throughout the lateral section. The solution reduced RSS control interventions, improved ROP by 47%, and significantly enhanced the speed and accuracy of geosteering versus offset wells. The successful integration of automated and customized drilling technologies represents a transformative step in ERD well execution, significantly reducing well time and increasing drilling efficiency. The scalable and repeatable nature of this autonomous downhole drilling solution offers a robust framework for future field development in similarly complex environments.

Abstract Monitoring reservoir saturation and water-flood progression is essential to optimizing production and injection strategies in mature fields. From a reservoir engineering perspective, methods like 4D seismic and electromagnetic surveys are used as the main evaluation techniques. Recently, advancement of LWD well-placement technologies has enabled identification and monitoring of remaining oil saturation while wells are being drilled. This paper elaborates a reservoir scale study on the utilization of LWD reservoir mapping and borehole imaging. The subject field has been producing oil since 1965 and utilizing peripheral water-injection since 1970. The main reservoir is a carbonate S-formation, from the Lower Cretaceous era (Aptian), which targets subzone layers A and Z. These subzones are typically 60-80 ft thick and differ in their permeability properties. The field has a complex geometry of a dome structure resulting from faulting and diapirism, lying under an undulated shale formation. Samples of eight recent wells, representing various geological settings on the field's crests and flanks, are elaborated in this paper. The main production sections were drilled in 6-in. horizontal hole, utilizing an LWD configuration comprising ultra-deep-azimuthal-resistivity (UDAR), high-resolution laterolog resistivity borehole imaging, density, neutron porosity, propagation resistivity and gamma ray sensors, in addition to a push-the-bit rotary steerable drilling system. The UDAR sensor provided 1D inversion reservoir mapping from deep measurements with 75 ft depth of investigation (DOI) and shallow measurements with 25 ft DOI, achieved by selecting spacings and electromagnetic frequencies based on a pre-well modelling study. UDAR provided far-field measurements whilst triple combo and borehole imaging logs acted as a near-field validator, resulting in a confident real-time interpretation for structural and fluid mapping. Various phenomena within each well were seen, such as water influx and water flood fronts. On average, geosteering actions through UDAR safely placed the well 20-40 ft TVD above the mapped water. Subsequently, 3D inversion from UDAR offered richer insight into the fluid distribution. Directions and dynamic movements of fluids were discovered from this 3D advanced processing. Information from borehole imaging data illuminated geological structural features. The comprehensive dataset was used as a basis to observe fluid behaviors and connections, representing current field conditions. Advanced utilization of LWD is not only limited to geosteering and geomapping applications in a single well but could potentially be expanded into reservoir-scale observation. Tracking remaining oil saturation and water movement is possible before wells begin production. This novel method enables a bridge between subsurface analysis at the reservoir and operational levels. It provides a timely understanding of the reservoir and helps to accelerate the design of future wells, reducing risk and eventually enhancing productivity or injectivity.