bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Natural Language techniques in Reservoir Management Framework
Authors: Vimercati Silvia , Vignati Emanuele , Mariotti Pamela , Severino Sabatino , Raimondi Lorenzo , Onzaca Christian 
Published: September 2022

Abstract
Reservoir Management requires the definition of a strategy that analyzes the risk assessment to identify surveillance activities and corrective measures. In Eni, a best practice has been established to regulate this strategy through the Reservoir Management Plan (RMP). This paper will present the application of Natural Language Processing (NLP) technologies to improve the definition of RMP. Results will be discussed, highlighting benefits and advantages in extracting cross-document information and running comparisons between different RMPs.
Natural Language Processing refers to the branch of computer science concerned with the ability to understand text and spoken words, like human beings. NLP algorithms have been applied to RMPs to pull structured information adding useful numerical data. The main strategy for managing unstructured data, re-elaborating information upon specific request and implementing cross-document queries are discussed. Hundreds of RMP documents have been collected, hoarding extensive information in compartmentalized storages. NLP algorithms can be applied to unlock this hidden potential by capitalizing lessons learnt between Business Units and partaking the experiences acquired in similar assets.
The information extracted from unstructured data includes insights on well and reservoir surveillance activities and corrective measures in different assets. A tool has been developed to enable a rapid screening of the key parameters in different assets, highlighting how similar risks can be mitigated. The tool analyzes documents and forms, looking for data and relationships among entities in the text. In particular, the NLP model extracts tables, table cells, and the items within and returns JSON formatted results.
This task is performed by using open-source NLP libraries and custom logic, in order to adapt common algorithms to RMP application. The procedure is orchestrated by a cloud based ETL (Extract Transform and Load) and data integration service to create workflows for moving and transforming data.
The workflow is scheduled and executed for each RMP document collected. Insights are collected and presented in a dashboard. Two main applications will be discussed to present the additional value brought by NLP algorithms in Reservoir Management. The mitigation strategies and relevant lessons learnt from analogues can be efficiently collected, analyzed and integrated in the planning and scheduling of reservoir management activities.
To the authors’ knowledge, this paper presents the first successful implementation of NLP techniques to Reservoir Management. Natural Language Processing algorithms allow unstructured data to be searched, organized and mined, highlighting the strength of combining data and leveraging the main insights without having to read through all the RMP documents.
System Engineering Recommendations to Improve Intelligent Completions
Authors: Nelson Ron , Handley Eric , Joubran Jonathon , Musayev Rashid , Patel Dhwani 
Published: September 2022

Abstract
This paper compiles recommendations from a broad range of sources into a single document to aid future intelligent completion installations and operations. While emphasis was placed on subsea completions, these recommendations can be readily applied to differing well types. Important differences between production wells and injection wells are addressed.
While it may appear that intelligent completion equipment can be treated as "commodity items" like many other completion components, this is not recommended. Intelligent completions are complex systems with design and operational requirements that span many engineering disciplines and impact many well components. Changing well temperatures and reservoir pressures generate unique and sometimes very challenging design conditions, with thermally-induced pressure gains in the control lines being an example. Failing to address all load cases, selecting the wrong control fluid, failing to properly clean even a single component, or employing the wrong operating practice even once, can permanently risk the integrity and/or operability of the intelligent completion.
This paper reviews each component within the intelligent completion and details a systemic approach for identifying risk and optimizing its design. The recommended process starts with the control fluid and methodically works through the rest of the intelligent completion components and processes. Systems engineering can lead to important insights to overall system specification, risks, and operating recommendations. Numerous recommendations and learnings from past projects are shared.
Additionally, the need to properly manage and operate the intelligent completion doesn't end with handover to Production. Recommendations for optimizing system longevity and diagnosing non-conformances are also provided.
A spreadsheet-based method of accurately assessing pressure gains in control lines is described, as are several recommended additions to the tree and other parts of the intelligent completion system. Explanations for anomalous behavior seen on several projects, which become clearer through the lens of systems engineering, are shared.
Principles and Advantages of High-Power Lasers for Descaling Surface Equipment
Authors: San Roman Alerigi Damian Pablo , Mutairi Saad , Batarseh Sameeh , Assiri Wisam 
Published: September 2022

Abstract
This work examines the physical principles and effects of high-power laser (HPL) descaling of surface equipment. This contactless technique can fully remove sulfide or calcium carbonate scale without compromising the integrity of the substrate. The method is environmentally friendly, waterless, and energy efficient. It could do away with chemical and mechanical methods for descaling, which have shown low efficiency treating fully-plugged deposits and environmental risks due to chemical use. This paper describes the process through an analysis of its efficiency and impact on the substrate material, the environment, and the implications to production reliability.
HPL descaling is described by a multiphysics approach that involves thermal and mechanical processes. The laser causes a phase-change on all or some of the constituents of the scale. This interaction results in spallation, dissociation, and at high energy sublimation. Laser-matter interaction is precise. It produces a small heat affected zone (HAZ) that decays exponentially away from the illuminated area. Thus, the effect of the laser on the surrounding material is minimal to none. Ultrasonic, multi-spectral imaging, microscopy, and statistical analysis are used to analyze the effect of the laser on the substrate material. The environmental impact of the HPL process is compared to existing methods; it is calculated via the carbon intensity of each step and supporting equipment involved in the processes, as well as by its impact to material reuse, waste reduction, and recycling.
Scaling can be detrimental to oil and gas production because it may hinder the flow of fluids from and to the well. In surface systems, scale deposits reduce the internal diameter of equipment, thus limiting flow-rate capacity and causing pressure drops across the production network. From a physics perspective, the process is effective because the energy can be delivered with extreme precision on the target. The efficiency of the process depends on the coupling of the HPL with the target and the rate of debris evacuation. The physics are complex but can be optimized through machine learning (e.g. reinforcement learning). The results of the comprehensive characterization demonstrate that HPL descaling preserves the integrity of the substrate. HPL descaling could increase the lifetime of surface equipment affected by scale, and hence contribute to reuse and recycling.
The adverse effects of scaling make prevention and removal crucial to the energy industry. Existing methods of scale-removal rely on mechanical or chemical scrubbing, which show varying degrees of success and may deteriorate the substrate. HPL descaling is an environmentally-friendly solution for production reliability; it enables complete descaling and the safe reuse or recycling of scaled equipment.
Utilizing Low-Density Mud Systems to Improve Operational Efficiency for Post Frac Cleanout of Unconventional Wells in Depleted Areas
Authors: Peurifoy David , McGraw Mike , Martinez Stephen , Morales Adrian , Farish Maddie , Perkins Reece , Merrill Allan 
Published: September 2022

Background
Due to advancements in horizontal drilling and completions technology, wells in some basins are now being completed in areas where conventional production has existed for 50+ years. This paper will focus on the Midland Basin, where wells in the Spraberry, Dean, and Wolfcamp formations have been produced since the 1960s and earlier in some cases. As a result, current unconventional wells in these formations will invariably deal with depletion. In the past, freshwater consisting of friction reducer and a foaming agent, along with nitrogen, was used to lighten clean-out fluids to a fluid density that allows circulation of these wells. The use of nitrogen, while necessary, can lead to variable fluid quality, increase clean-out times, add expense, and ultimately reduce time-to-market for these wells. Lightweight mud systems (LMS) are not new to the oilfield but relatively new to post-frac clean-out operations applications. The system consists of a proprietary water-based mud additive that reduces mud density by creating microbubbles encapsulating air in a multi-layer shell. This technology can reduce fluid weights by up to 1.9 ppg from the original base weight. The base fluid for the LMS may be freshwater, produced water, or brine. The fluids possess a low shear rate viscosity that allows good hole cleaning without risking formation invasion. The system may be used with nitrogen if needed for extreme cases. No degradation of mud motor performance has been observed when using the LMS. This paper will offer 3 case studies where the LMS provided operational and economic benefits in post-frac clean-out operations.
Gas Chemical and Carbon Isotope Composition as a Diagnostic Tool for Energy
Authors: Almubarak Zainab , Alrowaie Mohammad , Lu Feng , Algeer Ranya 
Published: September 2022

Abstract
As the world is moving toward a low-carbon energy structure, natural gas has become critical in the supply of global energy. The genetic identification of different types of natural gas is important for the assessment of their source and exploration potential. Chemical and carbon isotopic compositions of produced gas are useful tools to assess their origin, thermal maturity, migration and to monitor gas production. In this study, we present different geochemical approaches to assess the origin of the gases and thermal maturity as well as to evaluate the effect of adsorption on shale gas during production. Thirteen gas samples from different conventional reservoirs were analyzed for their isotopic compositions to assess gas origin and thermal maturity. To assess gas production, seven gas samples were collected periodically from the same unconventional shale interval and were analyzed for their isotopic signatures. The results demonstrate that carbon isotopic composition of methane to pentane can be used as fingerprinting tool to identify different sources of gas. The studied gases are all of a thermogenic origin and were generated from Type-II marine source rocks. Mixing of gases generated from different source rocks were observed. The mixed gases are characterized by similar isotopic profiles in methane and ethane and they differ in C3+ hydrocarbons. Thermal maturity trends were identified on the studied samples using the relationship between methane, ethane, and propane isotopes versus the wetness index (total HC/methane concentration). To study the effect of gas adsorption during production, samples produced from the same hydrocarbon source rock were assessed at different time intervals (one-year period of production). The results show small variations between isotope compositions; thus, the impact of adsorption is still uncertain and a longer-term monitoring plan is designed. The results of this study shed insight into using isotope geochemistry as an important diagnostic tool for natural gas exploration and production.
Separation of Oil and Water Emulsions: Is Heating Good Enough?
Authors: Gavrielatos Ilias , Mohan Ram S. , Shoham Ovadia 
Published: September 2022

Abstract
Surfactants and nanoparticles (NP) frequently act as stabilizers for oil and water emulsions. There is a need to investigate whether such NP stabilized emulsions (also known as Pickering emulsions) require different treatment for break-up, as compared to the well-known method to separate surfactant stabilized emulsions, i.e., heating. Thus, the main objectives of this work were to identify emulsions resistant to heating and develop a process able to accelerate the separation kinetics of such ultra-tight emulsions.
Extensive experimental investigations on the stability of different types of oil and water emulsions under various temperature and brine salinity conditions were carried out using a state-of-the-art Portable Dispersion Characterization Rig (P-DCR). The batch separator was equipped with a high-resolution, surveillance camera to monitor emulsion separation kinetics. Commercial grade mineral oil and synthesized brines with various salinities were used as the test fluids. Silica nanoparticles of different wettability and surfactants with different HLB values were deployed as the stabilizing agents for the produced emulsions.
It was found that the elevated temperature effects dominate the separation kinetics of the studied emulsions, as compared to any brine salinity effects, especially at higher temperatures, namely, 60°C and 80°C. Moreover, the effects of high temperatures and brine salinities on the separation kinetics were much more significant for the emulsions stabilized by surfactants than for NP stabilized emulsions. Perhaps more importantly, neither high temperature nor high brine salinity had any remarkable effects on the separation kinetics of the emulsions stabilized by hydrophobic NP. It was also shown that the hydrophobic NP dominate the stability mechanism for dual emulsifier fluid systems, such as emulsions stabilized by both hydrophobic NP (R974) and a surfactant of low HLB value (Span 80).
A novel oil-water emulsion break-up process was developed to enhance the kinetics of the separation, irrespective of the underlying emulsion stability mechanisms, namely, surfactant, NP or both. The performance of this separation process was superior to heating, which is the conventional method applied to separate oil-field emulsions. Finally, it is envisioned that the newly developed process may be applied in the field as an in-line separation system for tight oil-field emulsions.
High-Resolution Acoustic Imaging for Submillimetric Casing Thickness Quantification and Advanced Effective-Area-Based Burst Pressure Analyses
Authors: Simpson Greer , Littleford Tom , Battistel Anthony 
Published: September 2022

Abstract
For downhole casing integrity applications, high-resolution acoustic imaging is a novel approach for quantifying casing thickness, corrosion, and mechanical damage defects by measuring both inner diameter and outer diameter wall losses. The technology deploys high-density solid-state arrays with up to 512 transducers to achieve sub-degree azimuthal and sub-millimetric axial resolutions with casing thickness measurements down to a minimum thickness of 0.07 in with an error of ±0.005-in. In this study, we discuss the technological advancements, details of laboratory validation results, exploration of burst pressure calculation methodologies, and a field case study based on the novel technology.
The high-density solid-state transducer array uses acoustic signals to measure the casing thickness and radial measurements in a single pass. The resulting 3D point cloud of data is analyzed using image-processing-based machine learning algorithms. The validation data are collected from multiple machined and field samples. The machined defect dimensions are varied to test the detection, sizing, and accuracy of the platform. A field-based case study is presented to compare high-resolution acoustic imaging data with computed tomography scan data. To demonstrate the advantages and sensitivities of using high-resolution datasets and high-accuracy burst pressure methodologies, examples of RSTRENG software burst pressure analyses are provided.
The high-resolution acoustic imaging platform offers fundamental improvements over legacy magnetic flux leakage (MFL) and single-element ultrasound-based tools. Acoustic technology relies on direct measurement principles and results are not inferred through calibration. The time-of-flight-based approach enables the inspection a single casing string comprising different diameters, wall thicknesses, and materials in a single log run. The technology is pipe material agnostic and directly measures the casing thickness of ferrous and nonferrous metals. The electronic platform enables the capture and storage of submillimetric axial resolution, which provides details of the penetration profiles of all defects. High-resolution and spatially registered datasets are leveraged to conduct effective area, RSTRENG, and modified B31G burst pressure calculations with significantly improved defect identification, penetration quantification, interaction rule application, and shape characterization. The advancements presented in this paper are highly pertinent to gas storage and carbon sequestration operators, seeking integrity management advancements. The real-world benefits of the presented technology are the ability to extend well life, optimize workover schedules, and manage gas storage pressure ratings more efficiently.
Solving the Engagement Enigma
Authors: Smith Andrew L 
Published: September 2022

Abstract
The adoption of green credentials requires cultural change within our organisations and the need to attract, train, develop and retain a new breed of talent demanding a net zero future. This is fine in theory but one of the first objectives our industry must solve is the Engagement Enigma, otherwise none of these aspects will be achieved. This paper now provides a solution to solving the Engagement Enigma as it may be clearly demonstrated by the 4C's which show that the key process to ensure Engagement, is the underlying synergy created by starting a Career, acquiring Competence, demonstrating Care and a transparent feedback Culture created throughout an organisation by encouraging Continual Professional Development or CPD. We are therefore in the unique position to ensure that the oil & gas industry can also synergistically implement the IPIECA SDG's as an integral component of CPD to provide genuine engagement. The solution to the Engagement Enigma is a new paradigm which now clearly shows that to those skilled in the art it is self-evident that all the above UN SDG topics may be synergistically combined to provide us with a unique and novel solution to the Engagement Enigma.
Effects of Fluid Over Pump Intake on Rod Pumping System Performance
Authors: Ahmed Mohamed G. M. , Ahmed Ahmed Mohamed G. 
Published: September 2022

Abstract
The application of the reciprocating sucker rod pumping system has been growing steadily with the improvement in the system technology, which allows to open the application envelop of this system. Therefore, the need for a better understanding of the system performance is heavily required. Predicting the dynamic responses and loads is critically important to determine the operating situation, total system performance, and system output. Usually there is a perception of reducing the fluid level over the pump intake (intake pressure) will maximizing well production and system overall efficiency. This is not always true. In some cases, increasing fluid over the pump lead to more production, improving subsurface pump volumetric efficiency and improving system efficiency.
The main purpose of this study is to investigate the effect of fluid level over pump on the overall system and production performance.
In order to achieve that goal, the Sucker Rod Pump design simulator with actual field data has been used‥ The study analyzes the effect of well inflow, fluid PVT, pump size, setting depth, and running parameters. Actual field data are used.
This study concluded that for wells producing with pump intake pressure below bubble point, especially low productivity wells, reducing pump intake pressure does not always increase well production. It also concluded that negative effect on the net production and equipment running live, which is in additional to increasing power consumption and reducing overall system efficiency.
This study summarizes the results and lessons learned from successful use of system design and operation. The study provides practical recommendations supported by a series of case studies and multiple field examples where applying such approach increases the well production and net profit.
Automated Forensic PDC Dull Analysis Enables Digital Feedback Loop
Authors: Devers Cameron , Dyer Warren , Lyles Dustin 
Published: September 2022

Abstract
A digital feedback loop is designed to facilitate collection and analysis of cutter wear on a large scale, propelling improved engineering decisions. An increase in data-oriented bit engineering design strategies produce more predictable performance differentials as designs are iterated. The results of implementing the feedback loop are compared to previous methods across several metrics. The digital feedback loop implemented is based on the idea that all aspects of PDC bit design should be centered around the collection and understanding of analytic data, and not subjective data. This is made possible by utilization of automated data collection techniques taking measurements of dull bits for all repaired dulls. The data collected is then compiled for analysis while simultaneously made available to all relevant parties. This process is continuously repeated for every dull bit. The integration of the digital feedback loop is built into the bit product development process and application specific cutter and design selection workflows. This integration minimizes forensic dull evaluation time investment to the point where data is collected, processed, and uploaded to analytics tools within minutes of a dull being received via automated metrology technology integrated into the repair process. The trend analysis, additional models and insight gathered from enhanced data collection and recording has additionally reduced the time it takes for bit design to reach the design proposal stage by 60%, while simultaneously increasing the number of metrics that are considered during the product development design process. The reduced time spent in bit design has led to reduction in time between bit order received, bit manufacturing and subsequent bit delivery. The overall improvements generated by the integration of this digital feedback loop have also resulted in insights not previously considered or reviewed due to lack of access to the information. These improved, data driven insights have increased the accuracy of the design process to improve probability of performance objectives of the new design being met on the first iteration rather than a continuous trial and error-based approach. The process discussed in this work describes the utilization of an automated forensic dull bit evaluation methodology that allows for a data driven method of improving PDC Bit design and application specific cutter and bit design selection while working to minimize the necessity of the subjective, visual based analysis of the common industry methods.