bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of Seismic Attributes and Borehole Images for Exploring the Prospectivity of Late Jurassic and Early Cretaceous Carbonates in North Western Desert, Egypt
Authors: Osman Osama Abdelaziz , Hanafy Ahmed Gamal-eldeen , Nour Ahmed Mamdouh , Benyamin Mostafa Hussein , Mostafa Rabie Seddik , Eid Ramy Eid , Diab Hosni Diab , Redwan Mohamed Said 
Published: October 2022

Abstract
Seismic attributes play an important role in hydrocarbon exploration and production because they bring additional information about the lithological and petrophysical changes in the subsurface along the main seismic reflectors. Borehole images are commonly used to evaluate carbonates, particularly for qualitative and quantitative study of fractured and vuggy carbonate. The main goal of this study is to combine seismic attributes with borehole images to improve the confidence in mapping the fractured carbonate prospect.
The workflow started with an integrated formation evaluation that aims to identify possible promising zones based on wireline and mud logs. It then moved on to integrating borehole images with available core data and thin sections to analyze and interpret the reservoir lithofacies, as well as decoding possible diagenesis effects, with a focus on fracture identification and analysis. As a result, wells with the best reservoir quality were identified. Finally, structural mapping was completed using a combination of seismic features, including edge detection, coherence, and minimum curvature to find fracture areas.
The occurrence of fractured dolomite or vuggy dolomite was discovered in wells with prospective pays connected with oil and gas shows. It was also observed that borehole analysis for some wells shows that they have low porosity (3%). Seismic attribute maps around these wells, on the other hand, show a high fractured density, emphasizing that combining borehole images with seismic attributes is critical for evaluating these carbonates. Most of the fractures are oriented Northwest-Southeast and are linked to deformation zones. We also identified that several varieties of features and fractures collected from borehole images exhibit a strong link with discontinuities on the seismic amplitude, evident from the variance seismic cube, allowing us to pinpoint areas with high fractured density. Several carbonate prospects have been identified, with a high density of fractures expected.
Several carbonate prospects have been identified, with high fractures expected. Additional exploration for new carbonate reservoirs in the Western Desert will be enhanced by the workflow provided in this paper. This workflow also helped us in better-identifying carbonate prospects with high fractured density.
Optimizing Rig Scheduling Through AI
Authors: Thatcher Jimmy , Eldred Morgan , Suboyin Abhijith , Rehman Abdul , Maya David 
Published: October 2022

Abstract
Traditionally, a significant amount of time is invested in producing the most optimal drilling schedule to deliver the targets considering various constraints and changing priorities. This paper demonstrates how Artificial Intelligence (AI) can generate an optimal Rig Schedule while improving on conventional planning techniques. This includes adding additional value through increase in production, freeing up assets and reduction in fuel consumption, driving cost reductions further enabling supply-chain debottlenecking.
This paper presents a real-world application and solution of the general set of optimization problems such as the Knapsack Algorithm and Vehicle Routing Problems (VRP) for optimizing rig mobilization with added real-world complexities and constraints. A dynamic system allows more than just scheduling against demand/supply as it also self-calibrates the schedule through new real-time requests and real-time situation analysis based on location, availability, and other relevant constraints.
Based on in-house case studies conducted and compared with traditional approaches for rig scheduling and optimization, the presented solution can reportedly achieve a 99% reduction in time needed for generating key results. Compared to conventional drilling scheduling methodologies, there are no or minimal white spaces for the resource allocation strategies presented by the AI solution with a potential reduction in the asset utilization (with a reduction of 5%) along with being able to reduce total distance traveled and the fuel burned (carbon emissions) assuming standard mobilization patterns based on historical data, with a reduction ranging between 11-24% as a minimum depending on the scenarios selected.
This case study provides a novel approach to the scheduling of rigs that leverages artificial intelligence for complex fleet and schedule management that provides an opportunity to generate best plans to meet KPI's with significant reduction in assets required and fuel burned (energy efficiency) during mobilization; but also provides a higher level of input into operations and could in future provide real time input into operational activity plans minimizing overall costs and input to streamline supply chain from layers of conservatism.
Determination of Hydrocarbon Compounds in Rocks by Ultrasonic Extraction Gas Chromatography-Mass Spectrometry
Authors: Bao Junchi , Jin Wei , Wang Yusheng , Jiang Ge , Yan Yan 
Published: October 2022

Abstract
The convenient, quick and accurate detection of hydrocarbon compounds in rocks and the establishment of the detection method of hydrocarbon compounds in rocks are of great significance for the study of hydrocarbon compounds in rocks. It can provide effective parameters for the study of oil-source source correlation, sedimentary environment Identification and source layer determination. In this paper, We use conventional extraction (cable extraction) and ultrasonic extraction to extract hydrocarbon compounds from rocks respectively, using Gas chromatography mass spectrometer to analysis the extracts. Then we choose some of the more commonly used in oil and gas geochemical parameters for comparison, by comparing these parameters to compare the advantages and disadvantages and the difference of two methods, so as to analyze the extraction efficiency of ultrasonic extraction method, and constantly optimize the experimental conditions by experiments. By statistics and comparison of the geochemical parameters obtained by the two extraction methods, it can be found that ultrasonic extraction method can not only meet the demand of routine analysis, but also can get some parameters which conventional extraction method can't get. Ultrasonic extraction method has the advantages of low sample quantity, fast processing speed and high analytical efficiency. the analysis results are more accurate. Therefore, ultrasonic extraction gas chromatography mass spectrometry can effectively replace conventional extraction methods to analyze and process rock samples, obtain more accurate geochemical parameters and make the results of oil-source correlation more reliable, which has better geological significance.
A Workflow to Analyze Vertical Formation Heterogeneity and Optimum Geological Grid Layering Using Petrophysical Logs
Authors: Gerges Nader , Makarychev Gennady , Maarouf Alaa , Barillas Luisa Ana , Madhavan Midhun , Gore Sonal , Kloucha Chakib Kada , Mustapha Hussein 
Published: October 2022

Abstract
Integrated, multidisciplinary field projects require the transfer of large datasets and results from one discipline to another. Typically, petrophysical workflows for geological modeling produce only rock-types, porosity, permeability, and water saturation model logs. Petrophysical logs are upscaled to the fine geological model grid during the 3D modeling workflow. The geological model aerial cell dimensions and layer size are determined using geostatistical methods to optimize the run time during the dynamic simulation phase.
In this study, we propose to enhance the number of outputs from the petrophysical workflow by providing recommendations on the optimal vertical layer size by stratigraphic interval for capturing all relevant heterogeneities associated with complex carbonate reservoirs.
We assume that the deflections of the petrophysical logs (such as porosity or permeability) are symmetrical across the geological layer. This is a reasonable assumption for vertical and subvertical wells since the layer size should be comparable to the vertical resolution of the logs. Therefore, the inflexion points of the input log correspond to the facies changes. After identifying the layers’ borders, we calculate the thickness of each layer and its corresponding input log value.
The developed application was successfully tested using data from more than 200 wells of a giant carbonate reservoir from the Middle East. The results demonstrate that the developed algorithm parameters are easily adaptable to a variety of both different input log types and various ranges of petrophysical properties. The created interface interactivity enables the user to readily assess and alter parameters to optimize the layering scheme while capturing the right level of heterogeneities. During the testing on a real dataset, the developed application revealed vital information on the formation's vertical heterogeneity and the significant difference between distinct stratigraphic intervals. The provided analysis of layer thicknesses can be used directly for the creation of static model layering scheme.
The Critical Roles of Geomechanical Modeling During Exploration Phase
Authors: Hamid Osman , Oluyemi Gbenga , Sanaee Reza 
Published: October 2022

Abstract
Geomechanics has become an essential part of the petroleum industry's daily routine due to the increase in operational challenges when dealing with deep, tight, unconventional, and subsalt reservoirs, in addition to depleted zones and multilateral drilling in the direction of minimum stress. This research aims to provide innovative integrated geomechanical solutions during the exploration phase and investigate the relationship between in-situ stress, fractures, faults distributions, and fluid flow to correlate fracture variations to lithology changes.
This integrated approach will incorporate all available field data, including seismic velocities, petrophysical well logs, geological, and structural models that will be used to construct 3D geomechanical static models to assess and characterize the reservoir properties, such as reservoir quality index (RQI), sweet spot, reservoir compartmentalizations, pore pressure, in-situ stress regime, and presence of faults and fractures. The fracture properties and dynamic simulation will be conducted by studying the fracture properties from the core sample, image log interpretation, and fluid flow using Finite Element models
The results from this study will be used as a guideline during the field exploration phase to set the field development strategies and answer the question such as: How stress field variations will impact petroleum systems, fault seal integrity assessment, reservoir mapping, and heterogeneity, in-situ stress vertical and lateral variations and their impact on well placement and well spacing, and what types of geomechanical modeling that can be used to accurately drill a save and cost-effective wellbore to meet completion and stimulation requirements that maximize hydrocarbon production.
The studies showed that implementing this workflow has a huge business impact on reservoir developments by saving millions of dollars and minimized nonproductive time during planning and field development.
This workflow is special in a way that it will be calibrated and updated when acquiring new data at the exploration stage and througout the well life to yield better results.
Artificial Engineering Intelligence (AeI) - Connected Microservices for Drilling Optimization and Real Time Well Engineering
Authors: Samuel Robello 
Published: October 2022

Abstract
As we develop autonomous drilling system the setpoint operational and control, parameters for drilling are to be determined. The decision-making control loop performance should be faster. As the system with high aspect ratio i.e., length over diameter is highly stochastic, calculating the parameters for the optimal condition is very difficult. The paper presents methodology to obtain the envelop of sufficed, satisfied, and optimized engineering conditions resulting in "optosatisficed" condition aka "artificial engineering intelligence" which is good enough or an acceptable solution or a reasonable solution under the given condition.
The paper presents an adaptive model which connects different engineering models in the form of microservices for constraints rather than a complete theoretical optimal closed form solution-based model. The approach to be taken under this condition is to include the stability of the bit, drillstring and wellbore, which will result in the near optimum envelop (desired) for the drilling parameters. Important analyses are coupled - vibration-stability analysis and bit-wear performance analysis. The optimum rate of penetration limiting values are calculated as the well is drilled with specified interval by considering the bit wear and the vibration. At each drilled interval, it is assumed that the bit wears out continuously and the amount of wear depends on the uncontrolled and uncertain parameters such as formation, anisotropy, dip etc. Also, all the calculations such as hole cleaning mechanical specific energy are calculated continuously.
The analysis results have shown that the convergence was very quick in obtaining optimal solution and the predictability in the test wells have shown best solution results under uncertainty. Also, it has been found that the results provide reasonable threshold values when more and more data are used as the well is drilled. The stability envelop is shown in the figure with multiple connected engineering microservices. As long as the driller stays within the operational region, the results have shown that the operating parameters are satisfying and good enough solution for the desirable outcome. In other words, near normal engineering solution is achieved. Updating of the stability plot at every discrete drilled interval provides the pattern of the envelop for further decision-making set points for the controller in the case of an autonomous system.
This paper provides a new framework for faster decision strategy. Injecting life to the well design software itself will provide amazing power. When a well is designed or monitored or drilled, well plan can be made interactive so that user can optimize and take proper decision to drill ahead or automate the operation.
Quantitative Prediction of Lost Circulation Risk Ahead of Bit Using Leaky Noisy-Or Gate Bayesian Networks and Seismic Attributes
Authors: Yuan Duo , Lu Baoping , Haider Syed Tabish 
Published: October 2022

Abstract
Quantitative prediction of lost circulation risk ahead of bit is of great significance for mud loss prevention and well control. This paper provides a method that is able to not only locate the potential mud loss points along well trajectory to drill, but also estimate their severity and occurrence probability using leaky Noisy-OR gate Bayesian network and seismic-well data mining. All the risk factors of lost circulation are identified and then they are mapped into a Leaky Noisy-OR Gate Bayesian network to generate a conditional probability distribution table, so as to assess the lost circulation risk quantitatively ahead of bit. This method has been tested and applied successfully and these predicted results provide decision basis for preventing and dealing with the problems of lost circulation.
Practical Guide to Successful Wireline Formation Pressure Testing Across Highly Deviated and Depleted Sections
Authors: Franco Nata , Corona Mauricio , AlMahroos Mohamed , Kestring Thiago , Oliveira Adriano 
Published: October 2022

Abstract
Reaching bottom with logging tools is difficult when the well is highly deviated and has significant pressure overbalance. This often leads to mechanical and differential sticking risk on cable operations and the desired depth not being reached. The normal practice is to deploy formation testers on drill pipe (pipe conveyed logging – PCL). This paper aims to provide guidance to operators for performing safe and efficient wireline formation pressure testing jobs in challenging conditions, saving considerable rig time.
It is critical to understand the factors which cause tool obstruction and cable sticking. This helps to optimize the conditions needed for successful wireline operations and prevents high-impact events, such as tools getting stuck, fishing operations, wiper trips, cancelled logging and PCL jobs. The main contributing factors were analyzed and divided into different categories: well design and trajectory, borehole conditions and geomechanics considerations, drilling fluid properties and wireline equipment selection. A tailored operational workflow with detailed risk assessment with prevention and mitigation measures were combined into a practical guide and then it was implemented to perform a series of jobs.
Following the new systematic approach, wireline logging jobs could be safely conducted in several wells across 8-3/8" and 5-7/8" sections in a challenging drilling environment. The maximum inclination was 60° and maximum overbalance of 3,920 psi. The vast majority of planned pressure points were collected and there weren't held ups or overpulls observed during the operations. For the tester tool to reach the bottom, it was essential to have a proper well design and trajectory construction, good borehole quality with minimum disturbance and exposure, right mud weight selection together with fit-for-purpose drilling fluid and bridging plan.
All best practices and lessons learnt, were put together to a guide and made available to the project team for future operations. This technique was adopted as the new standard for logging through carbonates formations in deviated sections in the field, with high depletion. As operational costs are a concern in long deviated logging, optimization done using alternative methods offer benefits in terms of rig time and efficiency. If the main risks aren't assessed properly, then it incurs significant costs and inefficiencies.
This innovative multidisciplinary approach integrates different domains to perform wireline formation testing operations in a cost effective and time efficient manner when compared to running logs on drill pipe. This method will serve as a reference for operators and service providers to achieve step changes in similar operations. The key elements of this initiative will be described in detail in the paper.
AI-Assisted Thin Section Analysis, The Making of a Geologically-Realistic Digital Interpretation
Authors: Leseur Nicolas , Franco Alba , Xin Li , Yang Fan , Lokhanova Olga , Belouahchia Mounir , Belmeskin Rashid , Habibi Zaynab , Shebl Hesham , Tamimi Mohamed 
Published: October 2022

AbstractThe visual interpretation of geological thin section is a meticulous endeavor carried out by geoscientific specialists in order to ground truth log interpretation as well as guide the spatial distribution of properties required by reservoir simulation models. At the same time, the shortage of qualified personnel, the abundance of dormant core data and the requirements for increased reservoir model accuracy have created operational needs that human interpreters alone can hardly fulfill.In this context, a method for AI-assisted thin section interpretation was developed, leveraging the latest advances in the field of deep learning to provide geologists with a comprehensive set of reservoir properties derived from rock images. While a significant part of the solution relies on the training of supervised convolutional neural networks, establishing consistent labeling procedure, enforcing geological rules, removing input and output image artifacts and close communication with subject matter experts were equally critical ingredients to a geologically-realistic prediction as well as supplementing a scarce amount of input training data.The main outcome of this multi-step domain-knowledge and data science work not only led to an increase in the mean intersection-of-union metric but also to the assurance that fundamental geological principles were honored. In practice, the algorithm ensured that petrographic object detection was constrained by biostatistical population criteria as well as prohibit the occurrence of non-natural combination of nested framework grain.The aforementioned enhancements were subsequentially implemented and deployed at company scale for ADNOC's specialists to carry out their geological interpretation through conventional web-browser applications.
Improving Petroleum Real Options Calculation by the Application of Quantum Artificial Intelligence.
Authors: Setyabudi Heru , Kartowisastro Iman Herwidiana , Trisetyarso Agung , Abdurachman Edi 
Published: October 2022

Abstract
Regarding the issue of carbon gas and reducing fossil energy to environmentally friendly energy, an investor certainly needs an accurate calculation model with a fast calculation time for the adjacent investment portfolio. The smart energy concept integrates information and communication to improve overall efficiency. One of the fossil energies that is still the mainstay of energy today is crude oil. However, it has price constraints that have high volatility and there will be changes in business patterns in the oil and gas industry sector. Capital planning has been a struggle for Oil and Gas companies. Computing speed has increased dramatically, but there are still problems making reasonable computation times. The problem is in the field simulation in determining how much detail can be modeled to make it accurate but maintain fast calculation times. This is a popular topic in the Oil and Gas industry these days. Real Options Quantum Computing (ROQC) tries to find trends and information not seen by traditional methods, either the Discounted Cash Flow model (DCF) and the Real Option Valuation model, of course, representing new methods of work and analysis in the future. ROQC attempts to measure the risk associated with the financial success of a project as it relates to the accuracy of the proposed capital budget and costs as well as the speed which is processed near-realtime.