bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges and Opportunities for Green Hydrogen Power Supply in Oil and Gas Remote Facilities
Authors: Ruvalcaba Velarde Salvador Alejandro 
Published: December 2021

Abstract
The energy transition to renewable energy and hydrogen as an energy carrier, along with low-carbon footprint production targets in the oil and gas industry act as a catalytic for exploring the role of hydrogen in oil and gas production. For upstream and midstream operations, potential opportunities for using hydrogen as an energy carrier are being developed both in hydrogen generation (X-to-hydrogen) as well as in hydrogen consumption (hydrogen-to-X), but not without series of technical and economical challenges.
This paper presents potential use cases in upstream and midstream facilities for hydrogen generation and consumption, be it both from hydrocarbon processing resultant in what is called "blue hydrogen" or from integration with renewable energy to form what is called "green hydrogen". It also explains process integration requirements with diagrams for full-cycle green hydrogen use from generation to consumption and its interaction with renewable energy technologies to achieve low to zero-carbon emission power supply systems. Different hydrogen generation and conversion technologies are reviewed as part of the modeling process.
Green hydrogen feasibility is assessed in terms of operational efficiency and cost constraints. Hybrid hydrogen and renewable energy power supply systems are simulated and presented according to the intended applications of use in oil and gas facilities.
This paper provides a feasibility analysis and hydrogen technology integration potential with renewable energy for applications in oil and gas remote facilities power supply. It also shows emerging hydrogen technologies potential for use in upstream and midstream applications.
Artificial Intelligence-based Predictive Technique to Estimate Oil Formation Volume Factor
Authors: Kalam Shams , Khan Mohammad Rasheed , Khan Rizwan Ahmed 
Published: December 2021

Abstract
This investigation presents a powerful predictive model to determine crude oil formation volume factor (FVF) using state-of-the-art artificial intelligence (AI) techniques. FVF is a vital pressure-volume-temperature (PVT) parameter used to characterize hydrocarbon systems and is pivotal to reserves calculation and reservoir engineering studies. Ideally, FVF is measured at the laboratory scale; however, prognostic tools to evaluate this parameter can optimize time and cost estimates. The database utilized in this study is obtained from open literature and covers statistics of crude oils of the Middle East region.
Multiple AI algorithms are considered, including Artificial Neural Networks (ANN) and Artificial Neural Fuzzy Inference Systems (ANFIS). Models are developed utilizing an optimization strategy for various parameters/hyper-parameters of the respective algorithms. Unique permutations and combinations for the number of perceptron and their resident layers is investigated to reach a solution that provides the most optimum output. These intelligent models are produced as a function of the parameters intrinsically affecting FVF; reservoir temperature, solution GOR, gas specific gravity, bubble point pressure, and crude oil API gravity. Comparative analysis of developed AI models is performed using visualization/statistical analysis, and the best model is pointed out. Finally, the mathematical equation extraction to determine FVF is accomplished with the respective weights and bias for the model presented.
Graphical analysis is used to evaluate the performance of developed AI models. The results of scatter plots showed most of the points are lying on the 45 degree line. Moreover, during this study, an error metric is developed comprising of multiple analysis parameters; Average absolute percentage error (AAPE), Root Mean Squared Error (RMSE), coefficient of determination (R2). All models investigated are tested on an unseen dataset to prevent a biased model's development. Performance of the established AI models is gauged based on this error metric, demonstrating that ANN outperforms ANFIS with error within 1% of the measured PVT values. A computationally derived intelligent model provides the strongest predictive capabilities as it maps complex non-linear interactions between various input parameters leading to FVF.
Complex Stimulation Approach to Low-Temperature Carbonate Formation Revitalizes Bahrain Brownfield
Authors: AlJanahi Ahmed , Abdelrady Sayed , AlMannai Hassan , AlTawash Feras , Ali Eyad , Yudin Alexey , Al-Jalal Ziad , Guleryuzlu Metin 
Published: December 2021

Abstract
Carbonate formations often require stimulation treatments to be developed economically. Sometimes, proppant fracturing yields better results than acid stimulation. Carbonates are seldom stimulated with large-mesh-size proppants due to admittance issues caused by fissures and high Young’s modulus and narrow fracture width. The Magwa formation of Bahrain’s Awali brownfield is a rare case in which large treatments using 12/20-mesh proppant were successful after the more than 50 years of field development.
To achieve success, a complex approach was required during preparation and execution of the hydraulic fracturing campaign. During the first phase, the main challenges that restricted achieving full production potential in previous stimulation attempts (both acid and proppant fracturing) were identified. Fines migration and shale instability were addressed during advanced core testing. Tests for embedment were conducted, and a full suite of logs was obtained to improve geomechanical modeling. In addition, a target was set to maximize fracture propped length to address the need for maximum reservoir contact in the tight Magwa reservoir and to maximize fracture width and conductivity.
Sufficient fracture width in the shallow oil formation was required to withstand embedment. Sufficient conductivity was required to clean out the fracture under low-temperature conditions (124°F) and to minimize drawdown along the fracture considering the relatively low energy of the formation (pore pressure less than 1,000 psi). Understanding the fracture dimensions was critical to optimize the design. Independent measurement using high-resolution temperature logging and advanced sonic anisotropy measurements after fracturing helped to quantify fracture height. As a result of the applied comprehensive workflow, 18 wells were successfully stimulated, including three horizontal wellbores with multistage fracturing - achieving effective fracture half-lengths of 450-to 500-ft. Oil production from the wells exceeded expectations and more than doubled the results of all the previous attempts. Production decline rates were also less pronounced due to achieved fracture length and the ability to produce more reservoir compartments. The increase in oil recovery is due to the more uniform drainage systems enabled by the conductive fractures.
The application of new and advanced techniques taken from several disciplines enabled successful propped fracture stimulation of a fractured carbonate formation. Extensive laboratory research and independent geometry measurements yielded significant fracture optimization and resulted in a step-change in well productivity. The techniques and lessons learned will be of benefit to engineers dealing with shallow carbonate reservoirs around the world.
Gravity Survey of King Fahd University of Petroleum and Minerals Dammam Dome, Saudi Arabia
Authors: Soupios Pantelis , Stampolidis Alexandros , Fedi Maurizio , Kaka SanLinn , Al-Ramadan Khalid , Tsokas Gregory , Pasteka Roman 
Published: December 2021

Abstract
The study area is a part of Dammam Dome that is situated at King Fahd University of Petroleum & Minerals (KFUPM) campus, Dhahran, Kingdom of Saudi Arabia. The gravity survey was conducted as a pilot case study to explore part of Dammam Dome in greater detail.
Gravity data were collected solely during night hours due to low noise levels. A significant part of the survey was conducted during the summer holiday period, , when there was no student are on campus. A total of 235 gravity measurements were made using a Scintrex CG5 gravitometer, while a Trimble R10+ differential GPS (DGPS) was used to measure the stations’ location and elevation with the highest accuracy.
All gravity data were reduced using several algorithms, and their outcomes were cross-compared. The Complete Bouguer anomaly map for the campus was then generated. Several enhancement filters including edged detection and shallow to deeper source separation were applied. Data were inverted, and 2.5D and 3D models were created to image the subsurface conditions.
The main purpose of this study is to better understand the subsurface geology, tectonic settings of the Dammam Dome by applying the high-resolution gravity method before carrying out any comprehensive geophysical (seismic) 3D survey.
Advancement in Data Engineering and Feature Processing Workflow by Using Deep Learning Techniques for the Automation of ESP Failure Root Cause Analyses
Authors: Karnik Saniya , Yenuganti Navya , Jusri Bonang Firmansyah , Gupta Supriya , Nirgudkar Prasanna , Mohajer Mahyar , Malik Asim 
Published: December 2021

Abstract
Today, Electrical Submersible Pump (ESP) failure analysis is a tedious, human-intensive, and time-consuming activity involving dismantle, inspection, and failure analysis (DIFA) for each failure. This paper presents a novel artificial intelligence workflow using an ensemble of machine learning (ML) algorithms coupled with natural language processing (NLP) and deep learning (DL). The algorithms outlined in this paper bring together structured and unstructured data across equipment, production, operations, and failure reports to automate root cause identification and analysis post breakdown. This process will result in reduced turnaround time (TAT) and human effort thus drastically improving process efficiency.
Thermochemical-Pulse Fracturing of Tight Gas: Investigation of Pulse Loading on Fracturing Behavior
Authors: Al-Nakhli Ayman , Tariq Zeeshan , Mahmoud Mohamed 
Published: December 2021

Abstract
Unconventional and tight gas reservoirs are located in deep and competent formations, which requires massive fracturing activities to extract hydrocarbons. Some of the persisting challenges faced by operators are either canceled or non-productive fractures. Both challenges force oil companies to drill new substitutional wells, which will increase the development cost of such reservoirs.
A novel fracturing method was developed based on thermochemical pressure pulse. Reactive material of exothermic components are used to generate in-situ pressure pulse, which is sufficient to create fractures. The reaction can vary from low pressure pulse, to a very high loading up to 20,000 psi, with short pressurization time.
In this study, Finite Element Modeling (FEM) was used to investigate the impact of the generated pressure-pulse load, by chemical reaction, on the number of induced fractures and fracture length. Actual tests of pulsed fracturing conducted in lab scale using several block samples compared with modeling work. There was a great relationship between the pressure load and fracturing behavior. The greater the pulse load and pressurization rate, the greater the number of created fractures, and the longer the induced fractures.
The developed novel fracturing method will increase stimulated reservoir volume of unconventional gas without introducing a lot of water to formation. Moreover, the new method can reduce formation breakdown pressure by around 70%, which will minimize number of canceled fracturing.
Significance of Smart and Integration System Solutions in Maintaining Well Integrity
Authors: Mugharbil Mohammed , Al Khunaizi Mohammed 
Published: December 2021

Abstract
Well integrity is one of the most critical elements for extending the producible life of a well. A healthy well enables optimization of productivity, enhanced oil recovery, trial tests of new technologies, and much more. Factors such as external corrosive aquifers, internal corrosion, corrosive hydrocarbons, cement bond damage, solids and sand production, and others are considered the main integrity dangers worldwide. When well integrity is affected, not only economic risks but also risks to health, environment and safety are probable. Well integrity is an objective achieved by optimum design and construction of the well after studying and assessing all possible hazards; effective monitoring of the well behavior while it's under production; and timely intervention when an integrity problem is detected.
Evaluating all the aspects of well integrity during well operation is crucial. Cyclic surveillance is important to be followed, including wellhead pressures/annuli surveys, temperature surveys, corrosion logs, wellbore clearance, and well fluid samples, among other activities. With the help of smart and integrated systems, production engineers can have much better control over well integrity and be proactive in making timely decisions prior to any unforeseen events. The smart system keeps the well surveillance records, risk-rank the wells, and sets KPIs to tackle necessary actions wherever applicable. The developed system immediately triggers any threat on well integrity when it occurs.
A Diverse Set of Validation Experiments for Hydraulic Fracturing Simulators
Authors: AlTammar Murtadha J. , Sharma Mukul M. 
Published: December 2021

Abstract
In recent years, numerical fracturing simulation has seen an unprecedented emphasis on capturing the complexities that arise in hydraulic fracturing to better design and execute hydraulic fracturing jobs. As the need for more sophisticated simulators grows, so does the need for more sophisticated physical models that can be used to study the mechanics of the fracturing process under a controlled environment, and to validate the numerical predictions of advanced hydraulic fracturing simulators. We developed and utilized novel laboratory capabilities to perform an extensive set of fracturing experiments across various aspects of hydraulic fracture propagation including the effect of far-field stress contrast, rock mechanical heterogeneity, multi-well injection, borehole notching, fluid injection method, type of injection fluid, and interaction with natural fractures. Numerous direct observations and digital image analyses are documented to provide fundamental insights in hydraulic fracturing. As demonstrated through a few case studies from the literature, our laboratory experiments are very useful for validating hydraulic fracturing simulators due to the small-scale, two-dimensional (2-D) nature, controlled environment, and well-characterized properties of the test specimens used in the experiments.
New Workflow of Sediment Mass Balancing, from Local Datasets, for Predicting Basin Scale Trends
Authors: Michael Nikolaos A. , Zuhlke Rainer 
Published: December 2021

Abstract

Objectives/Scope
Sediment volumetric budget estimates are very important input parameters for process-based depositional modelling (forward stratigraphic modelling). This paper presents a new integrated approach for analyze sediment volumetric budgets in sedimentary basins that is based on the reconstruction of regional grain size trends. In subsurface studies of sediment routing systems, noticeable uncertainties in estimated total sediment volumes occur when available datasets are limited to local areas that do not cover the entire sediment routing system. These uncertainties also affect models of catchment areas, structural uplift, and denudation rates as well as net:gross predictions.

Methods, Procedures, Process
The new integrated approach focuses on reconstructing sediment budgets for entire sediment fairways from limited local datasets. It uses a combination of sediment mass balancing and local grain size distributions to predict basin-wide grain size distributions. The comparison of local grain size to fairway-scale grain size trends is key in correcting sediment volumetrics for significantly reduced uncertainties in catchment reconstruction and net:gross ratios predictions at the scale of sediment fairways, sub-basins, prospects and exploration/production fields.

Results, Observations, Conclusions
The new approach has been applied successfully to two subsurface continental to marine delta systems. They cover periods of approximately 7 My in total and include four limited local areas of interest (AOI). These local AOIs measure 200×200 km, while the entire sub-basin measures 500×800 km. The new approach indicates that only up to 40% of the total sediment volume of each fairway could be captured by previous methodologies with limited local areas of interest. A maximum of 70% of the entire sink sediment volume could be incorporated in local areas of interest. The new approach presented in this paper significantly lowers the uncertainties in sediment volume estimates, depositional rates and lithology distribution input parameters in forward stratigraphic modelling. For the two case studies, previous sediment flux models indicated rates of 10,000 km/Myr. The new integrated approach indicates that sediment flux actually reached 30,000 km/Myr with major implications for sediment distribution, net:gross prediction and catchment size and denudation rates estimates.

Novel/Additive Information
The new integrated approach reduces uncertainties in catchment size and tectonic exhumation rate estimates for clastic depositional systems. It provides lower uncertainty parameters (sediment volume, source locations, sediment fractions, diffusion coefficients) for forward stratigraphic modelling, e.g., for reservoir quality prediction in hydrocarbon exploration. In fundamental research, provenance analyses can be better constrained by improved catchment size prediction and sediment grain size distribution models for sink areas
Design of a Dislocation Well Pattern and Drilling of Shallow 3D Cluster Horizontal Wells for Development of Ultra Heavy Oil
Authors: Chen Peng , Yang Guobin , Chen Lei , Zhang Guobin , Han Haochen , Chen Chen 
Published: December 2021

Abstract
The Junin block in Venezuela was known as an ultra heavy oil belt reserved in extra shallow layers (950ft-1,380ft) with unconsolidated formations. A cluster wells platform drilling was required for the Field Development Program (FDP). Optimisation of the well pattern and drilling of shallow 3D cluster horizontal wells for development of ultra heavy oil are presented in this paper.
A well pattern of hand-shape dislocation was forwarded to enhance effective recovery of heavy oil in diamond blind area. Optimisation of the casing programs and control of the well trajectories as well as other key performance drilling were designed. A strict anti-collision barrier design and operation steps were worked out to assure the drilling safety. The loss-resistance, anti-collapse, stick-stuck proof, lubrication and reservoir protection were put into considerations for the drilling fluid design. Recovery of heavy oil was enhanced by means of electrical heating system.
Drilling challenges such as shallow target zones, big build-up rate, long horizontal sections, great friction drag and torques, and well trajectories control were experienced and settled. Especially the puzzles of well trajectories control in unconsolidated formations, great friction drag and torques of strings in large displacement long horizontal sections for subsequent operations, and the unstable wellbore were tackled. A typical well data revealed that the horizontal displacement vs. TVD ratio was as high as up to 4.5. The setting depth of surface casing and the determination of KOP were critical to the horizontal wells with large displacement in shallow layers. Pressurized combined drilling and casing-running by means of top drive overcame the drag and torque and achieved planned TD and casing setting depth. The use of electrical wireline heating rod increased the temperatures in and close to the wellbore, and compensated the radius heat loss and avoided viscosity increase of heavy oil so that the output was maintained and improved.
It was the first time for successful drilling of shallow 3D cluster horizontal wells with ratio of horizontal displacement vs. TVD over 3.5 in heavy oil belt of Venezuela. The innovative palm-shape dislocation of the well pattern design satisfied the demand of reservoir development and contributed to good production gain of heavy oil.
Artificial Intelligence Aided Proxy Model for Water Front Tracking in Fractured Carbonate Reservoirs
Authors: Zhang Yanhui , Hoteit Ibrahim , Katterbauer Klemens , Marsala Alberto 
Published: December 2021

Abstract
Saturation mapping in fractured carbonate reservoirs is a major challenge for oil and gas companies. The fracture channels within the reservoir are the primary water conductors that shape water front patterns and cause uneven sweep efficiency. Flow simulation for fractured reservoirs is typically time-consuming due to the inherent high nonlinearity. A data-driven approach to capture the main flow patterns is quintessential for efficient optimization of reservoir performance and uncertainty quantification.
We employ an artificial intelligence (AI) aided proxy modeling framework for waterfront tracking in complex fractured carbonate reservoirs. The framework utilizes deep neural networks and reduced-order modeling to achieve an efficient representation of the reservoir dynamics to track and determine the fluid flow patterns within the fracture network. The AI-proxy model is examined on a synthetic two-dimensional (2D) fractured carbonate reservoir model. Training dataset including saturation and pressure maps at a series of time steps is generated using a dual-porosity dual-permeability (DPDP) model. Experimental results indicate a robust performance of the AI-aided proxy model, which successfully reproduce the key flow patterns within the reservoir and achieve orders of shorter running time than the full-order reservoir simulation. This suggests the great potential of utilizing the AI-aided proxy model for heavy-simulation-based reservoir applications such as history matching, production optimization, and uncertainty assessment.