bluuebunny/crossref_metadata_2025 huggingface dataset:
Unlocking the Potential: Enhanced Field Development Through Integrated Analysis of Pre-Drill and Post-Drill Reservoir Data in a Giant Offshore Field, Abu Dhabi
Authors: Al Zinati O. , Alyan M. , Alzaabi M. , Almessabi W. , Howell A. , Alshamsi F. , Alteneiji A. , AlTamimi M. , Al Zaabi N. , Fazal A.
Published: November 2024

Intensive field development is being executed with extended reach Maximum Reservoir Contact (MRC) wells in a giant offshore field in Abu Dhabi. Given the drilling complexity in brown fields with various pressure regimes, the integration between static and dynamic reservoir data is crucial to ensure that wells are optimally placed in the right reservoir zone with an optimized performance. The process helps to identify opportunity generation, and thus maximizes asset value. The process is streamlined to become efficient covering multi-disciplinary aspects for hundreds of drilled wells.

For improved outcomes, the process typically is conducted about six months after the first production date. The degree of details included varies depending on the well objectives and the asset requirements. The process involves data-driven integration of static and dynamic data (well logs, production, pressure, etc.) obtained from a newly drilled well and compare them against pre-drill expectations. Digital platforms are utilized, and multi-disciplinary team members discuss the observations after proper compilation of the data acquired. All the observations, action items (including surveillance and mitigations plan), and recommendations are summarized, documented, and shared with entire Field Development Planning (FDP) team to learn from drilled wells.

The outcomes of the process have a significant impact on decision making of field development. The process enables identifying potential opportunities to maximize production and oil recovery of the field through optimizing well placement, well spacing, horizontal length, and completion designs. The values of information are clearly addressed from data gathered and surveillance activities to support FDP decisions. For example, production logging tools gathered assure production/injection and assess stimulation effectiveness in long reach laterals. Thus, deployment of Limited Entry Liner (LEL) designs for lower completion has been remarkably successful in facilitating cost effective stimulation to maximize areal sweep efficiency. Reservoir models are also assessed as part of the process by comparing them to actual observations to ensure their quality for optimal FDP decisions. Ultimately, implementing such integration can greatly optimize field performance, achieve anticipated production growth, and realize net impact.
A Machine Learning Model for Real-Time Early Kick and Loss Prediction EKLP Application
Authors: Zhang Shang , Samuel Robello
Published: November 2024

Early Kick and Loss Prediction (EKLP) is crucial in drilling operations to maintain well control and prevent catastrophic events such as blowouts. Real-time detection allows for immediate corrective actions, minimizing risks and costs. This paper presents a CNN-LSTM hybrid model, leveraging Convolutional Neural Networks (CNN) for feature extraction and Long Short-Term Memory (LSTM) networks for time series analysis. The model processes real-time data from various drilling metrics, including Rate of Penetration (ROP), Weight on Bit (WOB), Revolutions Per Minute (RPM), Standpipe Pressure (SPP), flow values, pump rates, and mud pit volumes.

Trained on a dataset of normal operations and confirmed kick/loss events, the CNN-LSTM model demonstrated high accuracy and speed in predicting abnormal events, significantly outperforming traditional detection methods. The model was integrated into a real-time monitoring system for practical applications, showing superior ability to process sensor data and predict kick and loss events. This hybrid approach enhances operational efficiency and decision-making in drilling.

In conclusion, the CNN-LSTM model provides a robust and reliable solution for real-time EKLP, combining the strengths of CNN and LSTM to handle complex drilling data. This approach improves detection accuracy and system adaptability, making it a vital tool for modern drilling operations. The model's potential to address other drilling challenges, such as stuck pipe events and drill bit fouling, further highlights its versatility and utility.
CCUS CO2 Injection Well Design Using Cloud-Based Software
Authors: Mwansa P. , Hassan M. Ali
Published: November 2024

World Nations agreed, under the 2015 Paris Agreement, to prevent increasingly dangerous and irreversible climate change impacts and limit global temperature rise to 1.5 degrees C above pre-industrial levels, which means cutting GHG emissions in half by 2030 and reaching net-zero CO2 emissions by mid-century in 2050. Carbon capture, utilization and storage (CCUS) on a grand scale is essential for the energy transition and achieving Net Zero objectives. In this aspect, it is crucial to ensure Fit-For-Purpose, safe and environmentally sound CCUS CO2 Injection Well Design.

This paper describes a process for CCUS CO2 Injection Well Design using a cloud-based software tool named WellDesign that has all regulatory well planning calculations in a single application with Open APIs to connect with third party applications and offering automation and efficiency in well planning & design. Will also present a design case that were performed during a Proof of Concept (PoC) test of digital well planning with a major Middle East national oil company.

Cloud-based computing allows businesses to use a system of remote servers hosted on the internet (the "cloud") to store, manage and filter their data. Instead of storing large quantities of data in on-premises servers. Using cloud-based software allows CCUS companies to create a more efficient and scalable work systems. It can also provide a centralized place to store and access unlimited data, making data analysis and data-driven decision-making much easier for teams within the company.
Design Considerations for Pressurized Flare and Vent Systems for Efficient CO2 Management
Authors: Rodrigues Hugo , Zaccheus Yemi , Seer Taseer
Published: November 2024

Carbon Capture, Utilization and Storage (CCUS) projects have gained momentum and are multiplying across the globe with more than 700 projects in various stages of development across the CCUS value chain. With the increase in carbon dioxide (CO2) related large scale projects, hazards must be well understood by the industry to avoid incidents that could hinder public acceptability or further development of these technologies. The hazard management of CO2 poses several risks such as physical property predictions, thermal expansion, low temperature, solid formation, corrosion, toxic effects, system vents and others.

This paper presents a discussion of the design challenges encountered in CCS and high CO2 gas field development projects. It introduces an innovative concept of flare segregation, which is not common in the petroleum industry but is expected to gain prevalence in the coming years with the expansion of CCS projects. Most commercial process simulators face challenges when it comes to handling high CO2 content at high-pressure conditions, such as those found with dense phase. Thermodynamic equation of state selection and solid formation prediction are key requirements for process simulation tools.

Design calculations show that the pressure maintained by the pressurized flare/vent can vary between 18barg to 6barg. The accurate assessment of this limit hinges on the precise prediction of the process-side fluid temperature, requiring an appropriate model of the thermodynamic and process system behavior. The subsequent Joule Thompson effect from the worst-case composition can be captured and used to calculate the tailpipe and header fluid and metal temperatures, as well as estimate dry ice formation. Design constraints such as flare capacity and API 521 15 min depressurization time may require staggering systems and procedural decreases in pressurized flare pressure.
Research on Substitution Path of Clean Energy for Production System in Oil and Gas Fields: A Case Study of Tarim Oilfield
Authors: Deng Qianxing , Wen Zhang , Ren Yongcang , Wang Kelin , Li Junyi , Guo Xinyong , Yong Xuemei , Xin Chen , Miao Xinyue , Zhao Zhiyong , Huang Chunjian , Gao Jieyu , Wei Zhiqiang
Published: November 2024

Under the goals of carbon peak and carbon neutrality, oil and gas fields enterprises undertake the tasks of oil and gas production and energy conservation and emission reduction. It is imperative to accelerate low-carbon transition and green development. However, energy consumption of production system in Tarim Oilfield Company of CNPC is mainly composed of natural gas and electricity, accounting for 92% and 8% respectively. Moreover, total energy consumption continues to increase, and the trend of carbon emission is rising under the existing production mode. Thus, clean energy such as solar energy, geothermal energy, and waste heat are utilized to produce clean electricity and heat energy. But the proportion of clean electricity and heat consumed is still less than 6% in structure of energy consumption. This is far from the transition goals of CNPC. It is urgent to speed up the development of clean energy to replace fossil energy consumed of production system.

The solutions and measures were determined after many discussions. Firstly, the demand of energy were reduced by energy-saving measures. Secondly, clean electricity and thermal energy were developed to increase the proportion of non-fossil energy in the energy consumption structure. Distributed photovoltaics and waste pressure of natural gas were utilized, and green electricity was purchased to decrease consumed grid electricity and natural gas. In order to cut down consumed natural gas, a method for selecting clean heating equipment was formulated, low-cost solar thermal equipment were developed and applied, and waste heat and low-temperature air heat were explored to recycle. Then, existing processes were electrified to build low-carbon oil and gas production system coupled with the characteristics of clean energy.

The results of cleaner production are very significant in the Oilfield. Overall, energy consumption was reduced by about 74,000 tce(tons of coal equivalent) and natural gas was replaced by about 4×107 m3 in 2023. As for green and low-carbon transition, while oil and gas commodities increased, total energy consumption and total carbon emission declined by about 2% and 3.5% respectively year-on-year. The electrification rate increased by 10% compared with last year. As for clean substitution, the production capacity equivalent of clean energy reached 53,000 tce, year-on-year rises of 114%. Clean heat consumption increased to 16,700 tce, a year-on-year increase of 108%. At the same time, clean electricity consumption increased to 7.4×107 kWh(kilowatt-hours), which was 615 times than that of last year. Then, six low-carbon demonstration areas and 10 carbon neutral wellsites or stations were built. As these measures are gradually implemented, it is expected that the results will be more obvious in 2024.
Total Emissions Estimation for Oil and Gas Production Facilities Using Aerial Gas Mapping LiDAR
Authors: Thorpe M. J. , Donahue C. P. , Kreitinger A. , Roos P. A. , Brasseur J. K. , Losby B. , Greenfield N. , Carre-Burritt A. , Kunkel W. M. , Altamura D. T. , Dudiak C. D. , Oberoi K. , Hengst V.
Published: November 2024

We present Gas Mapping LiDAR (GML) for methane emissions monitoring, mitigation, and informatics for oil and gas infrastructure. GML is deployed on small-manned aircraft for periodic monitoring to achieve high-accuracy and cost-effective detection, localization, and quantification of methane emissions. GML combines spatially scanned topographic and methane concentration LiDAR measurements with navigation data and aerial photography to create geo-registered methane plume imagery, LiDAR topography, and photographic mosaics. Data and results based on several years of single- and double-blind controlled release testing conducted with academic and industry partners is presented. Results demonstrate the high sensitivity LiDAR measurements allow detection of methane emissions at rates below 1.5 kg/h with greater than 90% probability of detection in most deployment conditions, allowing the detection of more than 90% of emissions from typical oil and gas production basins. The high spatial resolution of the LiDAR scans provides geo-location of emission sources, typically to within 2 m, for targeted LDAR response. The LiDAR methane concentration measurements, coupled with gas flow speed information, enable single-pass quantification error ranging from −65.6% to +78.9% (95% CI). However, when multiple plume measurements are aggregated from a set of facilities, total emissions rate quantification error below ±10% is achievable, supporting the development of accurate measurement-informed inventories. We present a method for estimating total emissions that combines models for interpreting individual source measurements and infrastructure data in a statistical analysis that is stratified by equipment type and facility class. We demonstrate the method by applying it to aggregated and anonymized emissions data from nine scans of 1350 facilities in the Permian basin and 320 facilities in the Eagle Ford shale play, spanning 2022 to 2023. Back-to-back scans of the facility sets are analyzed to evaluate the repeatability of the total emissions estimates relative to the uncertainty estimates produced by the method. A time series of total emissions from the two facility sets highlights the emissions reductions impact and cost-effectiveness of GML LDAR programs. In the Permian basin, annualized total emissions uncertainty for the scanned facilities was 24% in 2022 and 25% in 2023 with a year-over-year emissions reduction of 30% [7%, 54%] (95% CI). For the Eagle Ford shale play facilities, the annualized total emissions uncertainty was 13% in 2022 and 10% in 2023, with a year-over-year reduction of 20% [5%, 35%] (95% CI).
Reliability Study of Data Microchips for Downhole Data Acquisition Subjected to Pseudorandom Vibrations
Authors: Tella Sherif , Li Sanguo , Li Jibo , Zhan Guodong
Published: November 2024

Downhole data acquisition is a critical aspect of drilling operations for maintaining optimized and safe drilling conditions. However, the real-time downhole data readings while drilling are best captured using affordable drilling data microchips. Typically, microchips include an SoC (System on a chip), secondary memory, sensors, and an on-chip battery. But during drilling and releasing procedures into the well annulus, the data microchips may be subjected to random stresses that cause interconnects and components to fail, which ultimately results in damage, loss of stored data, and a low recovery rate after being released. Since random vibration loads can limit the efficient performance of drilling microchips, it is crucial to study the peak responses of the device when exposed to such stresses or a designed response spectrum. The development and validation of simulation modelling approaches is the initial step in this direction. This paper presents the numerical analyses and stress development mechanisms of the data microchips subjected to pseudorandom acceleration by a specified Power Spectrum Density (PSD). The highest computed RMS acceleration values are estimated to be about 25 g, 16 g and 18 g in the X, Y and Z directions respectively. However, assuming that the allowable peak value is thrice more than the RMS values, the peak acceleration can be evaluated to be 75 g, 48 g and 54 g in the X, Y and Z directions respectively. This indicates that there may be damage and loss of stored data on the memory chip. The permitted accelerations for the impacted components should be examined due to these high peak values which are more than the allowable vibration levels for downhole drilling tools. Hence, this device may require vibration absorber system. It is also necessary to estimate the margin of safety from the projected peak values. The pre-stress on the supporting unit is evaluated to be 60 MPa assuming 1 kN of force, the margin of safety is evaluated to be 7.6, 12.0 and 6.7 for the excitations in X, Y and Z directions respectively. In all excitations, the margin of safety is positive, indicating that the support might not break free from the housing unit and demonstrating how much stronger the support is than what is required to hold the actual vibration.
Novel Polymer Free Relative Permeability Modifier for Maintaining a Sustainable Water-Oil Ratio in Carbonate and Sandstone Formations.
Authors: Garcia Marieliz , Fragachan Francisco E. , Omer Mohammed
Published: November 2024

Water management strategies are applied to reduce water production from a reservoir, and often an increase in oil recovery is associated because of the wettability changes generated in the near wellbore area. The success rates of legacy water management strategies are low mainly because control of the water inflow is addressed at later stages when treatment effectiveness is less effective and the diagnostic for the source of water production is more difficult. Early reservoir management strategies are needed to effectively reduce unwanted water production.

This paper presents an integrated approach to characterize the problem properly, by incorporating an initial diagnosis from an intelligent monitoring tool that helps defines the nature of the problem followed by the injection of a novel relative permeability modifier – polymer free- characterized by a nano-particle system. The methodology involves the understanding of the reservoir current PVT (pressure, volume, temperature), performing a SARA (saturates, asphaltenes, aromatics, resins) analysis of the crude to define the colloidal instability index (CII). This CII, defined as the ratio of the SA to the RA, allows to determine where the precipitation of asphaltenes coating occurs; with a value below 0.7 defined as stable and a value higher than 0.9 as unstable. In oil reservoirs, when pressure falls below bubble point pressure the oil begins to release organics into the reservoir like asphaltenes. These asphaltenes begin to coat on the rock and negatively impact the porosity. The rock becomes oil wet.

The novel fluid system used is a colloidal suspension consisting of stabilized chemicals within a liquid phase. Due to their properties, they defy gravity forces and remain suspended within the carrier fluid in a random moving pattern. Shape, size, material, and concentration determine the effect of the fluid on specific application. The characteristics of such fluid systems were investigated through a series of core flood experiments to determine the effect of the fluid on the residual oil/residual water saturation and evaluate the water to oil ration (WOR) to determine the relative permeabilities.

This is a novel non-damaging technology which is independent of temperature and has been proven in more than 200+ wells in Latin America. The results demonstrated significant decrease on the water production and the WOR with enhancement in hydrocarbon production and proving zero damage on the oil producing zone. The solution proposed consists of the implementation of a recently developed analytical tool capable of integrating reservoir, completion, production, injection, and interventions history data, to diagnose the nature of the water production problem based on data analytics in conjunction with the novel technology to reduce the WOR.
Open Hole Gravel Pack Completion Through 7-5/8" Milled Casing Window for a High-Rate Gas Well, Offshore Trinidad
Authors: Douglas Dalton , Lutchman Deon , Ramnanan Avinash , Surajbally Rodney
Published: November 2024

The Angelin field lies off the Southeast coast of Trinidad. Development of the field commenced in 2018. The end of the useful life in certain wells created a chance to economically tap into the smaller reservoirs within the Angelin Field. This was achieved by repurposing and refurbishing the wellbores from the depleted wells. This process entails removing existing completion equipment (Decompletion), abandoning the previously exploited zone, and then drilling towards a new reservoir.

Sidetracking operations are performed to target the new zone. This is typically achieved by either cutting/retrieval of production casing or sidetracking of the current installed production casing. The decision is a factor of target location, production casing size and cement placement across casing sizes. Once the wells are drilled to TD, a new completion is installed.

The completion design is known as Slim Open Hole Gravel Pack completions, so-called ‘slim’ due to the reduced size of the lower completion section, which is required to pass through the smaller ID production casing.

Gravel packing has been employed in the Angelin field as the method of choice to manage sand production from unconsolidated and fragile subsurface formations in a high-rate gas environment. A distinctive characteristic of open-hole gravel pack (OHGP) compared to other sand control methods is its specialized screens. These screens contain ancillary shunt and transport tubes welded onto its core structure designed to achieving reliable sand control within the wellbore by providing alternative pathways for the gravel should there be any flow obstructions in the open hole. Although these features increase the reliability of the gravel pack job, they also introduce new potential failure points during installation to an already sensitive component of the well completion setup. Figure. 1Angelin Field offshore the island of Trinidad

Other critical components of the Angelin design include a fluid isolation device, gravel pack packer, gauge assembly and safety valve. Figure. 2Angelin Completion DesignFigure. 3Angelin Drilling Design

During the recompletion of one of the Angelin wells, the well was unable to be delivered as designed during well execution due to stuck pipe (production liner) above the reservoir interval which eliminated the initial plan of accessing the reservoir with the base case design. The option available for progressing the well was to access a shallower target across the stuck pipe via section milling or whipstock. The paper discusses the deployment considerations for both options and the eventual execution strategy used to successfully circumvent the high risks of deploying a slim-hole completion through a milled window.
Successful Underbalanced Well Completion Operations in Depleted Carbonate Reservoir of Brown Gas Field a Case Study
Authors: Haris Qureshi. , Sahir Inam. , Zulfiqar Anjum. , Sana-Ul-Hussnain Syed. , Ibtihaj Atiq. , Mudassir Khan. , Uzair Qadir.
Published: November 2024

One of the main goals for oil and gas operators is to optimize reservoir productivity and enhance the ultimate recovery from depleting fields. Underbalanced drilling stands out as a pivotal technology embraced globally to accomplish various objectives aimed at maximizing reservoir potential. Among these goals, the primary aims are to minimize formation damage, pinpoint favorable zones within the reservoir, and trim down overall well expenses. Drilling the reservoir section underbalanced but completing the well overbalanced significantly affects the overall productivity of the reservoir. In addition to that, well control and killing operations during drilling and completion phases exacerbate the issue, leading to prolonged well delivery timelines and escalated costs. In response, this study delves into the successful case study of the groundbreaking underbalance slotted liner running followed by underbalance completion operation.

The primary objective of this case study was to complete the well in underbalanced mode from dry hole to completion by utilizing the state-of-the-art technology which helps in bolstering well productivity without damaging the reservoir integrity, contrasting with conventional overbalanced methods. Methodologically, underbalance completion operations relied on the utilization of rotating control devices and downhole deployment valves for precise control, offering advantages such as enhanced reservoir connectivity while posing a few challenges which are also discussed.

Results showcased notable improvements compared to offset wells. The underbalanced approach reduced cumulative drilling and completion days by 25%, resulting in a cost saving of 17%. Most significantly, the comparison of flowing rates revealed a substantial gain of 34%, highlighting the efficacy of underbalance strategies in optimizing performance. The successful implementation of underbalance operations proved instrumental in achieving desired production rates by avoiding the extensive well killing operations and costly acid stimulation treatments, thus underscoring its pivotal role in reservoir management and productivity enhancement. This paper discusses the planning, design, execution, and lessons learnt in underbalanced drilling and completion operations in the subject field.
Examining the Corrosion Behaviour of Carbon Steel Pipelines with Bio-Corrosion Inhibitors in Sub-Sea Environments
Authors: Ayan Mohd , Garg Aaditya , Sharma Rohit , Agarwal Shilpi , Deka Barasha
Published: November 2024

This paper embarks on an extensive investigation into the corrosion behavior of carbon steel pipelines across aqueous environments. It aims to evaluate the effectiveness of bio-corrosion inhibitors, specifically focusing on beetroot powder doped with NaNO2, in bolstering the durability of these pipelines. The study encompasses a multifaceted analysis, including quantification of corrosion rates, and assessment of the inhibitor's impact on pipelines in various sub-sea fluid conditions. The combination of beetroot with NaNO2 presents a promising avenue for corrosion inhibition, aligning with sustainability goals and offering a potential solution to enhance pipeline longevity.

The research methodology employs immersion experiments with carbon steel samples to scrutinize their response across seawater environments. Bio-corrosion inhibitors are rigorously tested in aqueous samples using a wet immersion technique, wherein a solution of beetroot powder doped with NaNO2 is prepared. Experiments are meticulously conducted utilizing a 4 wt./volume % NaCl solution, with the churned beetroot powder doped with NaNO2 at varying loadings, typically ranging between 18% to 64%. The resulting inhibitor doped samples were tested through FTIR analysis and microscopic analysis, in order to understand the changes in the corrosion environment, and finally the corrosion measurement calculations, corrosion rate calculations and inhibition efficiencies were calculated.

The experimental findings unveil a substantial reduction in corrosion rates, particularly notable in seawater conditions (NaCl solution), where the combination of beetroot powder and NaNO2 demonstrates superior effectiveness. Visual observations compliments the significant decrease in corrosion by 47.2 wt.% with the utilization of the bio-corrosion inhibitor blend. This innovative approach not only offers a practical and environmentally friendly strategy for corrosion prevention in pipelines but also underscores the potential of organic inhibitors in mitigating corrosion challenges.

This study contributes novel insights into the efficacy of bio-corrosion inhibitors, shedding light on the synergistic effects of beetroot powder with NaNO2 in combating corrosion in carbon steel pipelines. The presence of organic compounds in beetroot, coupled with the corrosion inhibition properties of NaNO2, enhances the protective capabilities against corrosion, thus showcasing the potential of natural substances in corrosion management. Understanding the performance of bio-corrosion inhibitors across diverse environmental conditions is pivotal in devising tailored strategies to optimize pipeline durability and ensure reliable operation in varying contexts.
Plunger Lift Working Cycle Optimization using a Dynamic Full-Cycle Model Coupled with Simultaneous Perturbation Stochastic Approximation (SPSA) Algorithm
Authors: Chen Mai , Zhu Jianjun , Cao Guangqiang , Li Nan , Wang Haoyu , Zhu Haiwen , Jia Min , Yang Xiaopeng , Guo Donghong
Published: November 2024

This paper presents a novel approach to optimizing plunger lift operations in gas wells through the development of an improved dynamic model and an efficient optimization algorithm. We introduce an enhanced plunger lift mechanism model that integrates reservoir dynamics using classic production relationships, such as Vogel's Inflow Performance Relationship (IPR), and accounts for variable plunger velocities. The model combines a two-phase component approach for liquid and gas with a black oil model, improving the accuracy of fluid property estimations and providing a versatile simulation tool. To address the limitations of traditional optimization methods, we implement an improved Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. This allows for real-time, intelligent optimization of critical plunger lift parameters, including cycle duration, plunger ascent time, and control valve status. The optimization method is applied to both dual-cycle and quad-cycle plunger lift scenarios. Results demonstrate significant improvements in net present value (NPV), with increases of 65% for dual-cycle and 98% for quad-cycle operations, without modifying underlying reservoir or fluid models. The model's key operational parameters show strong agreement with commercial software results, validating its accuracy and reliability. This research contributes to the advancement of plunger lift technology by providing a more accurate dynamic model and an efficient optimization methodology. The proposed framework offers valuable decision-making support for field operations, potentially leading to substantial improvements in production efficiency and economic outcomes in gas well operations.
Leading the Way: Surveillance Planning and Integrated Interpretation for the First Low Tension Gas (LTG) Flooding Pilot in North Oman's Carbonate Field
Authors: Das Anindya , Al-Amri N. , Al Abri M. S. , Mahruqi D. , Abuawad A. , Itua O. J. , Ghufaili A. , Abram P. , Groenenboom Jeroen , Kahrobaei S. , van Batenburg Diederik , Abdullah I. , Al Bimani S. A.
Published: November 2024

The LTG approach employs surfactants to reduce the interfacial tension between water and oil, facilitating the mobilization of residual oil alongside foam for effective conformance control. This pilot was initiated to gather data to address critical remaining uncertainties and threats militating against full maturation of the opportunity. This paper sheds some light on the outcomes and insights extracted from the surveillance log data that played a crucial role in affirming if the first Oman foam pilot for LTG flooding is a success. Surveillance logging data played a pivotal role in determining the distribution of injected fluids and quantifying fluids saturation over the trial period. Advanced pulsed neutron technology and injection logging data from two wells within the carbonate field were utilized for the evaluation.

The injection strategy for two wells comprised multiple cycles of immiscible Water-Alternating-Gas (WAG) injection using N2 to establish a baseline, succeeded by multiple cycles of Surfactant Alternating Gas (SAG) injection for foam generation. A comprehensive surveillance program was deployed for continuous monitoring of pressure responses, saturation profiles, injection conformance, and reservoir fluid dynamics, enabling a thorough assessment of the SAG flooding process. Injection Logging data was undertaken for conformance monitoring during the injection phase. Analysis of pressure and temperature data was performed before and after injections to identify any potential occurrences of crossflow during shut-in phases. Additionally, advanced pulsed neutron data was acquired to monitor changes in gas, oil, and water saturation over time following each injection stage.

Interpretation of petrophysical advanced pulsed neutron and injection logging data, aided in assessing saturations within the relevant formations both before and after injections. Additionally, the injection logging data provided insights into injection intervals, assisting in the evaluation of fluid injection, and facilitating the planning of subsequent injection phases. The integration of these findings enabled one of the key project objectives to establish if foams can be generated during this LTG pilot process to be addressed.

The pre job planning and real-time support for data acquisition, rush interpretation, and integration of findings enables the team to efficiently strategize operations at each injection. Successful integration of pulsed neutron data and PLT data with the help of advanced log interpretation helped to establish that foam was generated from Low-tension gas flooding process in the carbonate reservoir.
Multi-Scale Fracture Modeling and its Application: A Case Study of the Zhaotong Shale Gas Demonstration Area in Southern China
Authors: Liu Yang , Xian Chenggang , Huang Xiaoqing , Liu Yunyi , Liu Mingyang , Wang Jianjun
Published: November 2024

The study area has been influenced by multiple phases of tectonic movements, resulting in complex geological structures characterized by fractures of various phases interweaving and embedding. This complexity has led to suboptimal outcomes in shale gas fracturing development. To accurately describe the fracture systems in the study area, this paper employs a multi-scale fracture modeling approach based on the comprehensive application of multidisciplinary data, including geophysics, geology, logging, and geomechanics. We established a three-dimensional model of natural fractures at three scales: seismic Facies fractures, discrete fractures, and diffuse fractures. This model was validated using imaging logging, drilling data, and microseismic monitoring of hydraulic fracturing. The model can be effectively used for the integrated analysis of drilling mud loss, fracturing operations, and productivity testing, thereby enhancing the effectiveness of fracturing operations and supporting the efficient development of shale gas in the study area.
A New Slimhole LWD Imager for Hostile Downhole Environment: A Kuwait Story from Deep Jurassic Tight Carbonate Rock
Authors: Al-Azmi M. , Al Ajmi S. , Al-Ajmi H. , Al-Hashash M. , Joshi G. , Al-Otaibi F. , Al Saadi D. M. , Shadad N. , Alraish A. , Pasaribu I. , Chambers B. , Shrivastava C. , Lashin Y.
Published: November 2024

Tight carbonate reservoirs of north Kuwait present many challenges for field development due to the inherent low porosity and permeability characteristics. The reservoirs are characterized by an average matrix porosity from 2 to 6% and permeability from 0.01 to 1.5 md. Near critical gas and volatile oil fluids produce mainly from Middle Marrat carbonate multi flow unit reservoirs. Natural fractures play a primary role in the producibility of these reservoirs and understanding the fractures and rock texture are important to the characterization and subsequent stimulation strategies for production.

High deviated well is commonly used to intersect the potential natural fractures and connect the multi flow unit inside Middle-Marrat carbonate. Multiple pressure regime encounter from the upper part of Jurassic layer resulted in the required 6in slimhole to be used to drill the target Middle-Marrat formation. Drilling risks are aplenty in downhole conditions made hostile by high viscosity synthetic mud with high solid content for a 6-in deviated hole going through varying pressure profile amidst high torque and drag. These challenges and slimhole size often limit the technology availability on acquiring high quality measurement especially with a borehole imager for fracture characterization.

The new logging-while-drilling (LWD) tool presented in this paper overcomes these challenges while delivering services in 18 to 19 lbm/gal (ppg) of synthetic-oil-based-mud (SOBM). The tool features an extremely compact 5 ft long LWD sub, which includes a power source, memory and directional sensors for azimuth and high side offset detection. The compact size sub allows for placement near the bit and reduces overall required bottom-hole-assembly (BHA) length. The torque and drag of the logging run in the cleaning out assembly were studied to ensure smooth acquisition minimizing risk of stuck pipe.
An Integrated Machine Learning Algorithm for Unconventional Flowing Bottomhole Pressure Prediction During Dynamic Gas Lift Operation
Authors: Jin Miao , Emami-Meybodi Hamid
Published: November 2024

Machine learning algorithms have been used to predict flowing bottomhole pressure (FBHP), but past research often neglected data characterization, affecting accuracy. We developed an integrated ANN model by embedding and categorizing multiphase flow physics to improve FBHP predictions under varying conditions. We collected data from 16 deep shale oil wells in the Permian Basin, Texas. Inputs for the machine learning model were derived from multiphase flow physics analysis, including oil/gas/water gravities, injection depth, wellhead pressure and temperature, well temperature gradient, liquid flow rate, gas-liquid ratio, and water-oil ratio. The physics-based ANN model was created using a simulation dataset and field data, while the data-based ANN model was developed directly from the 16 wells. Both models predicted FBHP for four new wells over their entire period and one new well with early months’ data. We also explored the combination of an unsupervised clustering model with the physics- and data-based ANN model for FBHP prediction.
Integration Of Innovative Real-time Extra-Deep Mapping Technology Maximizes Reservoir Exposure And Increased Production Potential Of A Complex Reservoir - A Successful Case History From The Largest Onshore Field, Libya
Authors: Al-Ansari Yusuf , Mumtaz Asim , Potshangbam Sanathoi , Hameed Mahmoud , Alaogali Issa , Elwirfili Ibrahim , Elsteil Mohamed , Ezarrug Nabil , Alkelani Khaled , Al Shlib Abdelhakim , Ezwai Jamal , Almuntafeky Ali
Published: November 2024

Exploiting the full potential of a complex reservoir in Libya's largest oil field is inherently challenging due to variable reservoir characteristics such as thickness, heterogeneity, water height uncertainty, and sub-seismic faulting. These geological complexities can significantly hinder effective navigation and optimal placement within hydrocarbon-bearing zones, necessitating the utilization of advanced reservoir navigation tools. This paper highlights how advanced geosteering technology can overcome complex reservoir challenges, leading to better well placement and increased hydrocarbon production.

To achieve the well objective, it is critical to optimally land the well in the target zone, mitigating the challenges due to geological uncertainty. Drilling further in the lateral section requires maintaining the trajectory in the best reservoir properties while tracking the Oil Water Contact (OWC) below for any elevation changes. A feasibility study based on offset data respecting the area's geological setting was undertaken to determine the best fit-for-purpose technology. Extra Deep Azimuthal Resistivity (EDAR) technology was identified as the optimal solution to detect resistivity contrasts remote from the wellbore, thus avoiding penetration.

EDAR ultra-high-definition (UHD) real-time inversion analysis facilitated the precise mapping of multiple resistivity layers and accurate delineation of the Oil Water Contact. This ensured well-informed and proactive geosteering decisions to land the well and expose the reservoir optimally. The EDAR inversion continuously mapped the top of the target zone along with the local dip variations, interpreted sub-seismic faults, and defined their throw. This technology was essential for maintaining a precise and smooth trajectory in a geologically complex area, achieving 100% reservoir contact, and optimizing hydrocarbon recovery. The information acquired from the inversion summary, such as resistivity distribution and structural changes, is valuable input for enhancing the field development plan of the area.

The use of advanced geosteering tools improves navigation accuracy in complex reservoirs, setting a new benchmark for challenging environments.
Digital Dexterity: Building Capabilities in the Era of AI
Authors: AlFedaghi Hadla S.
Published: November 2024

Technology is synonymous with change. From the industrial revolution to the digital age, each technological advancement has reshaped the way we work, live, and interact. Today, we stand on the precipice of a new era, driven by artificial intelligence (AI) and digital transformation. Establishments that fail to adapt to these changes risk obsolescence, while those that embrace digital dexterity—the ability to adapt, adopt, and use technology for better outcomes—position themselves for sustained success. Digital dexterity is defined as the ambition and capacity to use technology for better business outcomes [1]

Statistics underscore the importance of digital transformation for organizations. According to a 2023 Gartner report, 91% of businesses are involved in some form of digital initiative, and 87% of senior business leaders say digitalization is a company priority [1] Moreover, McKinsey & Company found that companies integrating digital capabilities are 23% more profitable than their less-digitized peers [2] Furthermore, organizations with high digital dexterity report a 37% higher employee productivity and a 30% increase in employee satisfaction [2]

Digital capabilities are essential for modern businesses. The incorporation of advanced digital platforms and platforms can streamline operations, enhance decision-making, and foster innovation. Organizations that prioritize digital transformation are better equipped to respond to market changes, optimize processes, and deliver superior customer experiences. For example, predictive maintenance powered by AI can foresee equipment failures before they happen, reducing downtime and maintenance costs significantly. Additionally, AI-driven analytics help optimize drilling operations, leading to more efficient resource extraction and better decision-making [3]
Resilient and High -Performance Multi-Medium Multi-Channel Wireless Long-Range Mesh Network for Offshore Automated and Remote Communication
Authors: Yahya M. , Abidin W. F. Zainal
Published: November 2024

High-speed Internet has been a very challenging implementation for offshore automated applications and remote communication to reduce operating costs significantly. The satellite network is commonly used in offshore operations, but its high latency and low reliability can be unsuitable for mission-critical operations. Another network medium, like digital microwave radio (DMR), is also commonly used in offshore operations to provide communication networks to multiple remote locations using a mesh configuration to extend the network range up to thirty kilometres. DMR has physical limitations, such as limited antenna height that limits line-of-sight wireless transmission range, regulated maximum bandwidth, and spectrum utilisation. However, decreasing the transmission bandwidth can increase the DMR transmission range, resulting in lower data speed. Overcoming the constraints of DMR as the wireless network solution for offshore, a multi-channel DMR configuration can be implemented to compensate for the lower data speed when transmission bandwidth is reduced. Many solutions in the market provide built-in aggregated data transmission using multi-channel DMR systems, but the solutions are restricted with small spectrum utilisation and high degradation of aggregated data transmission when hopping over multiple network nodes. A non-aggregated multi-channel data transmission method is an approach to mitigate such limitations. It is a cost-effective solution for multi-channel DMR systems. It can be agnostic and is independent of any wireless medium and type that can be used as a network channel and combined into a multi-channel wireless network system. The non-aggregated multi-channel data transmission controls the appropriate amount of data packets and the right time to transmit the data packets over all channels. The parallel data transmission is seemingly concurrent at microsecond time. The solution can improve network performance, reliability, and latency during severe weather conditions due to long-range and multiple network hops with parallel transmission paths. The solution has been implemented and used successfully at numerous offshore sites in the South China Sea using multi-medium and multi-channel wireless with significant performance results.
TransUNet: Accelerating Multiphase Flow Prediction in Geological Carbon Storage Systems
Authors: Tariq Zeeshan , Feng Zhao , Hoteit Hussein , Abualsaud Moataz , He Xupeng , AlMajid Muhammad , Sun Shuyu , Yan Bicheng
Published: November 2024

Deep learning-based surrogate models provide an effective alternative to numerical simulations for addressing subsurface multiphase flow challenges, such as those encountered in Geological Carbon Storage (GCS). In this study, we implemented deep learning based surrogate model as an alternative to complex GCS simulations using TransUNet, an enhanced U-Net architecture that incorporates Transformer models. TransUNet predicts the spatial and temporal evolution of CO2 plume saturation and pressure buildup in saline aquifers by leveraging the capabilities of Transformers. TransUNet is designed to effectively extract features from the structured data, considering spatial relationships and leveraging the Transformer architecture to capture both high-level and detailed information concurrently. Initially, we established physics-based numerical simulation models to account for both injection and post-injection periods of GCS. Employing Latin-Hypercube sampling, we generate a diverse range of reservoir and decision parameters, resulting in a comprehensive simulation databases. We train and test the TransUNet model on two different datasets: a radial model to establish a code benchmark, and the 2D complex model to validate the performance efficiency. Throughout the TransUNet training process, we utilize Mean Squared Error and the spatial derivative as the loss functions. The TransUNet model demonstrates robust performance on the radial model, achieving an R2 of 0.9982 and 0.9963 on testing dataset for saturation and pressure buildup predictions, respectively. Similarly, the model with updated hyper-parameters exhibits comparable performance on the 2D complex model, with R2 values of 0.9986 and 0.9967 on testing dataset for saturation and pressure buildup predictions, respectively. Notably, the Normalized Absolute Error (NAE) for all mappings consistently hovers around 1%, indicating the effectiveness of the trained models in predicting the temporal and spatial evolution of CO2 gas saturation. Moreover, the prediction CPU time for the TransUNet model is significantly lower at 0.02 seconds per case compared to the physics-based reservoir simulator's, 2500 seconds per case for the radial model and 1500 seconds for the 2D complex Cartesian model. This underscores the capability of the proposed method to provide predictions as accurate as physics-based simulations while offering substantial computational timesavings.