bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Near Seabed Velocity Modeling Techniques for Shallow Water OBN data
Authors: Li Yifan , Wang Wei , Hu Xin , Ding Chengzhen , Lyu Xiaolin , Gao Jiangtao , Khdhaouria Mourad , Rouis Lamia 
Published: May 2024

Summary
As is well known, modeling of the near-surface plays a significant role on the subsurface imaging, reservoir characterization, and monitoring. Usually datum static correction is rarely applied in offshore data processing due to stable velocity of the water layer with the assumption of homogeneous layering below the water bottom. However, in some shallow water ocean-bottom node (OBN) data, the complex seabed topography and significant velocity changes near the seabed caused by complex sediments (such as mud volcano) that could affect the subsurface imaging and structural interpretation. This paper proposed a solution to build a near-seabed model using shallow-water OBN data, which can obtain an accurate velocity model near the seabed and achieve significant imaging improvement in Cheleken PSA Area in the southern Caspian Sea.
Combination of Dissolvable Technology with Hydro Sub for Onshore Upper Completion in UAE
Authors: Bangun Antoro Robertus , Al-Rahma Rahma , Raman Abdul , Habib Hamzah 
Published: May 2024

Abstract
The slickline retrievable plug or an intervention-less plug is normally used in onshore upper completion procedures for hydraulic packer setting and pressure test tubing integrity. These are to provide a closed system of the completion string before packer setting and tubing test takes place. This paper approaches the need of advancements in operational safety, efficiency, and effectiveness. The technology focuses on the results providing good lessons learned and analysis of the combination of a dissolvable technology with hydro sub technique to answer the need.
Evaluation of dissolvable technology with a hydro sub, therefore, is an in-depth analysis for its application in real-life situations. The field trial results underline the success of implementation by proving its efficiency and effectively in running, setting and safety of upper completion operation. Insights from this trial will contribute lessons into the challenges and opportunities that are associated with the integration of dissolvable technology and a hydro sub technique.
The technology has been successfully deployed in operations carried out by the Abu Dhabi National Oil Company (ADNOC). This implementation by ADNOC provides an interesting case study into the adaptability and applicability of the dissolvable technology with a hydro sub in the context of the UAE onshore oil and gas sector sites. These positive results confirm the safety and efficacy of the combined approach in a way that it has the potential of revolutionizing onshore upper completion methodologies.
The paper presents empirical contributions to the field and also illuminates the practicality and reliability of technology dissolvable with hydro sub, hence enlightening the greater oil and gas community who are on a lookout for innovative solutions to onshore upper completion challenges.
A Gauss-Newton Inversion Based Automated Approach Towards Efficient Single Well Numerical Reservoir Transient Modeling
Authors: Kumar Arvind , Wydiabhakti Tety Benedicta , Nukala Sai Teja , Lopes Velerian Sanjao 
Published: May 2024

Abstract
Single Well Reservoir Modeling (SWRM) is typically utilized in the early stages of exploration for productivity estimates and optimizing completion strategies. However, its effectiveness is hindered by limited petrophysical and dynamic pressure data from single or a few wells in the block. Various methods have been developed to enhance the reliability of SWRMs for more accurate forecasts. This study presents a new technique for concurrently estimating key reservoir parameters - horizontal and vertical permeability, skin, and boundary distances - and their spatial distribution within the grid cells of a three-dimensional SWRM. The goal is to leverage interpretation results from standard pressure transient analysis of well test data as prior information for this complex inversion problem.
The methodology begins by creating a layer cake geological model based on petrophysical analysis of logging data, adjusted using interpretation results from well test pressure transient analysis. This is followed by systematic flow simulation of field well test operations in the layer cake model to generate model pressure data, which typically differs from acquired well test pressure data. To ensure convergence, a cost function is defined that combines both the well test pressure data and the model pressure data. This cost function relies on reservoir parameters such as horizontal permeability, vertical permeability, skin, and boundary distances, which must be refined for a pressure history match. An inversion approach is introduced to simultaneously refine all these reservoir parameters in an iterative manner to minimize the cost function. Importantly, the inversion methodology is closely regulated by a multiphase fluid flow simulator, which solves implicit black-oil fluid-flow diffusivity equations at each iteration to calculate the error between model pressure and acquired well test pressure. A range of minimum and maximum values for each property is provided to the inversion scheme to ensure a renewed distribution of reservoir parameters at each iteration. These parameters are then used to drive an error scheme guided by the cost function. A Gauss-Newton (GN) inversion method, supported by a regularization technique, facilitates the redistribution of properties across the geomodel grid cells. To improve the accuracy of inversion results, the initial parameters provided to the solver are thoroughly evaluated and, if necessary, adjusted through uncertainty parameter optimization (UPO).
This proposed technique offers a faster and more reliable approach to redistributing reservoir parameters in a homogeneous layer cake geomodel, introducing much-needed heterogeneity. This systematic redistribution not only enhances the reliability and credibility of a geomodel but also establishes a strong foundation for production forecasting strategies.
A New Supervised AI Logging Lithofacies Identification Technique and its Application in K Oilfield in the Middle East
Authors: Wenwen Yu , Xin Chen , Jianxiong Dong , Xiuyan Wang , Fuli An , Bo Wang , Dengyi Xiao , Zichang Tang , Lu Lv , Yuchen Liu , Jiajia Li , Yaliang Xia , Weixiang Zhong 
Published: May 2024

Abstract
Lithology identification is a very important task in reservoir characterization. Through the identification of lithofacies, we can know the state and distribution of oil and gas in the underground reservoir, and provide the basis for oil and gas exploitation and transportation, which is helpful to improve oil recovery and production efficiency.
With the development of oilfield, the exploration and development of lithological oil reservoirs become more and more important, and well log lithofacies identification has gained greater significance in reservoir characterization. Conventional well log lithofacies identification faces challenges, due to limited core data and low-quality log curves such as missing local well log curves, wellbore collapse, and anomalous log responses in fault zones. To improve the accuracy of well log lithofacies identification, a new supervised AI technique for well log lithofacies identification was proposed in this study.
The workflow mainly includes the following 5 steps: 1) Integrated lithofacies identification based on core description, thin section, high-quality well log, FMI, and CMR; 2) AI well log conditioning based on the high-quality well log curve intervals are selected as learning and training samples; 3) Sensitive log curves were chosen and cutoff were determined based on core-based lithofacies analysis and cross-plot analysis; 4) Log lithofacies identification for no core intervals based on sensitive well logs deep-learning; 5) Two method for lithofacies identification result QC, one method is using cored wells as a blind test well, the other method is using multiple wells to do comparative analysis.
This supervised AI logging lithofacies identification technique has been successfully applied in the K oil field in the Middle East. Blind cored well validation indicates that supervised AI well logging facies identification results have a high matching accuracy of 97%, enabling high-accurate and efficient well log facies prediction. Multi-well comparisons demonstrate that the well logging facies identification results in consistent with each other, and match with the results of sequence stratigraphic analysis in the study area.
AI-Driven Green Optimization in Well Construction: Carbon Emission Management Through Technical Limit Performance Benchmarking
Authors: Amadi K. W. , Alsaba M. T. , El Achkar J. H. , Elgaddafi R. M 
Published: May 2024

Abstract
Drilling operations generate CO2 emissions from diesel fuel used to power generators and other equipment on drilling rigs as extraction activities create around 10-15% of total energy-related emissions globally, an equivalent of 5 billion tonnes of greenhouse gas emissions. Improving operational efficiency is crucial for reducing overall emissions and combating climate change. Therefore, recognizing more efficient approaches and solutions with reduced carbon footprints is essential in creating future business continuity. This paper presents the application of machine learning optimization techniques in carbon emission management through technical limit performance benchmark. A Machine Learning (ML) model utilizing basic drilling parameters such as weight on bit (WOB), rotary speed (RPM), penetration rate (ROP), and torque (TOR) was used to estimate instantaneous Unconfined Compressive Strength (UCS) within the technical limit of operational performance across the different Lithologies. Supervised learning algorithm with 70:30 data splits using four ML algorithms, including Random Forest, support vector regression, artificial neural network (ANN), and Categories boost, was utilized in the prediction. The estimation was then leveraged to determine the maximum achievable penetration rate baseline for various lithologies based on rock drillability. Enabling a comparative assessment between actual drilling performance against an engineered technical limit drill rate performance as well as the expected greenhouse gas emissions (GHG). A case study using a field dataset showed that the models predicted instantaneous UCS based on the low- cost drilling parameters other than using the high-cost well-log and core sample techniques. Prediction accuracy was within the acceptable margin of error with CatBoost and ANN as best predictors, with correlation coefficient (R2 ) values of 0.75 and 0.77, respectively. The defined baseline performance benchmark improved drilling performance by 30-60% with a reduction in CO2 emissions across the project by 20 tCO2e emissions, equivalent to a 50% reduction in carbon emissions. The result of this research is essential for the continuous improvement in drilling carbon emission, performance monitoring, and improvement of overall drilling performance.
Unveiling the Dynamics of Proppant Migration in Fractures Through Numerical Simulation
Authors: Xiang Xiaolong , Han Guoqing , Ma He , Liang Xingyuan , Wu Qingxia 
Published: May 2024

Abstract
The migration of proppant within fractures directly affects the distribution pattern of the proppant, which is closely related to the effectiveness of hydraulic fracturing operations. This paper unveils the dynamics of proppant migration in fractures through numerical simulations and control variable method. The fundamental theoretical model shows the basis of simulation, and the Euler-Euler method is employed as the fundamental numerical calculation technique. The CFD software Fluent is chosen as the numerical simulation tool, and the three-dimensional modeling module is used to construct a fracture model. The turbulent model within Fluent is used, with defined computational methods and parameter settings, including construction parameters and fracturing fluid coefficients, which form the foundation of the entire flow simulation. Comparative experiments are conducted using the controlled variable method to observe the simulated results of experimental groups and study the morphological changes of the sand bed formed by the proppant particles after adjusting the variable parameters. The correlation between proppant particle migration and key factors, including injection plans and fracturing fluid parameters, is comprehensively examined, analyzed, and summarized. These findings unveil migration patterns of proppant particles within fractures, shedding light on the dynamics of proppant migration in fractures.
Geomechanics-Aided Successful Execution of a Challenging Build-Up Section Through Mixed Lithologies
Authors: Saber Rayan , Qahtani Faisal , Baghdai Ahmed , Sen Souvik , Chakrabarti Prajit 
Published: May 2024

Abstract
This study presents an example of geomechanics-aided successful delivery of a challenging 4100 ft long build-up section through mixed lithologies, towards minimum horizontal stress direction. The primary challenge in the build-up sections of the studied offshore exploration field in the Middle East was the mechanical instabilities of the weak shales which contributed to extensive tighthole, pack-off, backreaming, and therefore significant non-productive times. Other associated challenges were the differential sticking tendencies in the porous sandstone layers, and partial to total loss risks within the carbonates. The optimization roadmap comprised adequate mud weight design by geomechanical modeling in the planning phase, and real-time geomechanics advisory in the execution phase. The in-depth analyses of offset wells provided critical insights regarding the commonly occurring and potential drilling hazards across various formations. The post-drill geomechanical modeling and wellbore stability analysis of offset wells, calibrated with drilling events-based observations provided a clear understanding of the collapse pressure behavior of various formations. Based on the geomechanical modeling, a safe mud weight window as well as the minimum required mud weight were recommended to tackle mechanical instabilities. Real-time monitoring of the LWD data, aided by right-time geomechanical advisory support ensured successful well delivery. The drilling and the final BHA pull-out were completed without any mechanical instability issues which annulled the requirement of consecutive reaming trips, saving additional rig days. Successful completion of the challenging build-up section parallel to the Shmin azimuth registered zero NPT with notably improved drilling performance.
Review of Remedial Cementing: Techniques, Innovations, and Practical Insights
Authors: Shokry Amir , Mahmoud Ahmed Abdulhamid , Elkatatny Salaheldin 
Published: May 2024

Abstract
Effective cementing plays a pivotal role in ensuring the integrity of oil and gas wells, providing mechanical support, fluid containment, and environmental protection. This paper presents guidelines for conducting wellbore cementing remediation processes effectively, emphasizing longevity while minimizing environmental impact and safeguarding groundwater. The discussion encompasses factors influencing successful remedial cementing, including cement slurry properties, pumping methods, and squeeze equipment. Common techniques such as squeeze cementing and perforation/plug back operations are examined in detail, highlighting their challenges, considerations, and cost implications. Moreover, technological advancements such as polymer gels, silica gels, and self-healing cements are explored for their potential in addressing persistent challenges in sustaining casing pressure and ensuring cement sheath integrity. Through a comprehensive examination of remedial cementing practices and innovations, this paper offers valuable insights for industry professionals striving to optimize well integrity and operational efficiency while mitigating risks and ensuring environmental responsibility.
Fishing Job Optimization: Accelerating & Increasing of Successful Fishing Job Through Digitalization PHR Fishing Complexity Calculator
Authors: Proboseno N. G. , Sangka N. B. , Benigno A. Y. , Fadilah H. , Kurniawan J. , Bastian M. , Hutama A. F. , Kesnawaty D. A. 
Published: May 2024

Abstract
Fishing operations are complex and time-consuming. This is due to the associated uncertainty with the orientation and condition of the tool that requires fishing. Fishing usually is needed when least expected and brings a sudden halt to operations, especially if the downhole tools become stuck. Reaction planning begins at this time unless the project was planned properly from the outset. That reaction planning is not good is not the question. What is important is to establish the facts. What should be done to free the stuck? What will the cost be? This paper addresses these questions. It also emphasizes the importance of routine, continuous, but often unrewarded, effort by operation personnel.
An innovative approach to evaluate success ratio for retrieving a fish, not only using risk factors in the decision-making but also economical view is called PHR Fishing Complexity Calculator. Decision-making processes involved in recovering the fish when the downhole tools are stuck. The goal is to provide a usable wellbore at the lowest ultimate cost. Nowadays, the world is working in industrial revolution 4.0, where all are about digital transformation, increase the automation, artificial intelligence, and more simple work process. To keep the existences and explore the optimization in Industrial revolution 4.0, Oil and Gas Industry must be adapted and accelerated day to day operational in line with the advances of technology. Drilling & Well Intervention as an essential part of puzzles in Oil and Gas Industry which responsible not only to maintain the health of the wells but also make a guarantee the longevity of wells performance. The objective of this paper is to show the digitalization and simple workflow using PHR Fishing Complexity Calculator can maximize both quality and delivery time of fishing job "as simple as in your hand".
As a result, the success of fishing job can be increased from 39% to 71%. Approximately five wells can be converted into production and fish in holes can be retrieved. The success of those fishing jobs not only increases the satisfaction of fishing job but also increases production up to 153 Bopd and 2.9 mmscfd.
Moreover, the Drilling & Well Intervention Manager often is forced by an extended fishing operation to choose between the known costs incurred with abandonment of retrieval attempts and the unknown costs of continuing fishing operations. The successful manager makes the decision that costs the company the least money. Continuing fishing operations beyond some economic limit is a failure, even if the fish is retrieved and that portion of the hole saved, because more money has been spent in the fishing attempt than would have been spent by not fishing. The strategy is to minimize losses.
Simulating Horizontal Well Matrix Acidizing and Contrasting the Outcomes with Actual Data from Coiled Tubing PLT and DTS
Authors: Elhadidy Ahmed Ayman , Thabet Samuel Adel , Bereak Ahmed Said , Hanu Wael Mouhamed , ElAzhary Ahmed Adham , ElKaragi Alaa Osama 
Published: May 2024

Abstract
Carbonate reservoirs have different approaches to acid stimulation techniques. In order to achieve the most effective results, it varies by utilizing different diverters, acid systems, and pumping types. Even after improving the coiled tubing placement and numerical model predictions, it was previously challenging to determine where the injected fluids actually went during a stimulation job; therefore, the outcomes were frequently ineffective.
This scientific paper aims to investigate and contrast the Kinetix Matrix simulation software results of horizontal well matrix acidizing with actual data obtained from coiled tubing production logging and distributed temperature sensing techniques. The comparison with real-time data helps validate the accuracy of the simulations and provides valuable insights into the field application of this acid stimulation technique.
Beyond Traditional Ultra-Deep Resistivity: Advanced Applications Enable Comprehensive Reservoir Understanding
Authors: Fouda M. , Bikchandaev E. , Taher A. , Maimani A. Al , Al-Zawad A. 
Published: May 2024

Abstract
Ultra-deep ElectroMagnetic (EM) inversion is used to resolve multiple layers at a distance from the wellbore. Since it primarily responds to resistivity variations, it has been used for mapping formation boundaries and fluid away from the wellbore, such information has been key for improved well placement decisions and mapping the reservoir boundaries and areal extent. Enhancements in LWD Ultra-deep technologies and processing techniques including reservoir visualization in three dimensions, and inversion for anisotropy provide new applications for these technologies. As more advanced uses are developed it is important to shed some light on the integration of some of these unique cases.
Real-time transmission of nine ultra-deep resistivity components allows 3D inversion for both resistivity and anisotropy far away from the wellbore. Inversion for resistivity and anisotropy in three dimensions provides a solution for multiple reservoir challenges such as azimuthal well placement as well as lithology identification at a distance, differentiating different lithologies that have similar resistivity responses. Faults showing resistivity contrasts can also be mapped at distance from the wellbore. Inverting for the 3D volume using a smaller scale cell size has enabled resolving thin layers in real time. Finally, the integration of near and far field resistivity and 3D has improved far field petrophysical understanding in carbonates and clastic reservoirs.
Ultra-Deep Resistivity has been used in real-time to identify fluid and lithology at distance, this is critical to understand the proximity to fluid contacts or the presence of fluid barriers, such information is key for well placement decisions and completion design. Enhanced processing techniques has enabled resolving thin beds down to 1-2 ft thickness using Ultra-deep Resistivity 3D Inversion which compliments the visualization away from the wellbore and improves real-time decisions. Faults mapped at a distance provided an understanding to water encroachment behavior in carbonate reservoirs. It has also provided key information along with 1D and 3D for far field petrophysics, utilizing offset data and the information provided by the Ultra-deep resistivity inversion. This Paper covers all the challenges that deep and Ultra-deep Resistivity can cover from optimizing the well placement to formation evaluation in the far field.