bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-Purity, CO2-Free Hydrogen Generation from Crude Oils in Crushed Rocks Using Microwave Heating
Authors: Yuan Qingwang , Jie Xiangyu , Ren Bo 
Published: September 2021

Abstract
While the demand for hydrocarbon resources has been continuously increasing in the past 150 years, the industry is, however, criticized for carbon dioxide (CO2) emissions and concomitant global warming concerns. The oil and gas industry also face growing pressures in the ongoing energy transition. Generating and producing hydrogen (H2) directly from petroleum reservoirs has the potential to mitigate environmental impacts while revolutionizing the traditional petroleum industry and enabling it to become a clean hydrogen industry.
This paper proposes a novel approach to generate high-purity, CO2-free hydrogen from the abundant oil and gas resources in petroleum reservoirs using microwave heating. In this work, laboratory experiments were conducted to validate this scientific proof-of-concept and examine the roles of crushed rocks, catalysts, and water/oil ratio in hydrogen generation from crude oils in a reactor. A maximum of 63% ultimate hydrogen content is obtained in the generated gas mixtures, while the original CO2content in all experiments is negligible (&lt;1%). Catalysts can promote hydrogen generation by accelerating rate and locally enhancing microwave (MW) absorption to create ‘super-hot spots'. Water also participates in reactions, and additional hydrogen is generated through water-gas shift reactions. The water-oil ratio in porous rocks affects the ultimate hydrogen yield. Overall, this research demonstrates the great potential of using MW heating to generate high-purity, CO2-free hydrogen from in situ petroleum reservoirs. Further research and wide application of this technology would potentially transform petroleum reservoirs to hydrogen generators, thus mitigating the environmental impacts of traditional petroleum industry while meeting the increasing demand for clean hydrogen energy. This technology would also benefit the safe transition towards a decarbonized society.
Design, Development and Installation of Modular Inflow Control Technology
Authors: Erives Valeria , Plooy Mike , Agnihotri Vivek , Dikshit Ashutosh , Kumar Amrendra , Gurbanov Seymur , Tripathi Abhinandan 
Published: September 2021

Abstract
Integrating a flow control sliding sleeve into a sand screen can provide multiple advantages to the user in controlling the production inflow. Although it does come with an increased completion cost as well as the number of interventions required when its time to operate those valves. Especially in long horizontal wells, this can become time consuming and inefficient. A few technologies exist to address this issue but they are either too complex or require specialized rigging equipment at the wellsite, which is not desirable. As described herein, a unique, fit for application modular sliding sleeve sand screen assembly with dissolvable plugs was developed that eliminates wash-pipe and allows flow from several screens controlled via a single sliding sleeve. Design and field installation of these modular screens is presented in this paper. The new modular sand-screen consisted of an upper joint, modular middle joint, modular middle joint with ICD/SSD (w/ optional dissolvable plugs), and a lower joint, and novel field installable flow couplings between them. The design allowed for any number of non-ICD/SSD screen joints to be connected to any number of ICD/SSD joints in any order. A computer-aided design was followed to achieve all the operational/mechanical requirements, Computational fluid dynamics (CFD) was used to optimize the flow performance characteristics. Prototypes were manufactured and tested prior to conducting successful field trials.
The conceptualization and design stage provided several challenges as different ways to achieving modularity and interconnectivity were explored (such as internal to the tubing or external, sealing methods, ease of installation, reliability). Several design calculations were performed to select the most robust design and most suitable solution for the application. Design for manufacturing review, design calculations and CFD analysis helped with the selection of a concept that maximized the flow rates and kept flow velocity under the limit through the critical sections. Dissolvable plugs were used to temporarily close the SSD ports for wash-pipe free installation. The sealing mechanism of plugs was confirmed by differential pressure test up to 500 psi. A valuable, new downhole modular screen design for use w/ICD/SSD providing intervention-less completions without involving complex/expensive technologies is developed, tested and installed. A new, field-proven, modular sand control technology allowing flow from several non-ICD/SSD screen joints to drain into a single ICD/SSD joint, thus eliminating the need to run ICD/SSD on every screen joint in an unconsolidated formation is developed. Dissolvable plug integrated into sliding sleeve ports allowed wash pipe free installation. The technology allows increasing/decreasing the total drainage length at the well site per zonal requirements, thereby reducing costs and improving performance.
A Hybrid Petroleum Fiscal System for Investment in the Exploration and Production E&P of Hydrocarbon
Authors: Ogolo Oghenerume , Nzerem Petrus , Okafor Ikechukwu , Abubakar Raji , Mahmoud Mohamed , Kalu George 
Published: September 2021

Abstract
Globally, there are two types of petroleum fiscal system; the concessionary and the contractual petroleum fiscal system. The main differences between the two types of petroleum fiscal system is the ownership of the resources and some distinct fiscal terms. The contractual petroleum fiscal system specifies a cost recovery option and profit oil split unlike the concessionary petroleum fiscal system that allows the contractor to recoup his capital before payment of tax. This tends to increase the risk associated with the host government revenue as investment in the production of hydrocarbon is filled with uncertainties. There is a need to redesign the concessionary petroleum fiscal to enable it reduce the risk associated with the host government revenue by making the host government to earn revenue early from petroleum investment. This research therefore evaluated a hybrid petroleum fiscal system for investment in the exploration and production of hydrocarbon. The concessionary petroleum fiscal system was adjusted to include a cost recovery option. Petroleum economic model for investment in a typical onshore oil field was built using spreadsheet modelling technique with the fiscal terms in the hybrid petroleum fiscal system embedded in it. The cost recovery option and oil price in the model were varied between 0-100% and $20-$100 per barrel. The NCF, IRR and payout period of the investment were determined. It was observed that the lower the cost recovery option, the higher the host government revenue. From the profitability analysis of the investment in the hybrid petroleum fiscal system, it was observed that when the price of oil was $100/bbl, the NCF of the host government was $9146 and $8426.3 for 0% and 80% cost recovery option. The lower the cost recovery option, the higher the payout period and the lower the internal rate of return. Though lower cost recovery increased the host government revenue more but it may make the hybrid petroleum fiscal system unattractive for investment in periods of low oil price. Hence a higher cost recovery option was recommended for the use of this type of petroleum fiscal system.
Bit Design Methodology to Mitigate High-Frequency Torsional Oscillation
Authors: Tipples Rob , Keshiyev Sahet , Sheikhrezaei Kian , Centala Prabhakaran 
Published: September 2021

Abstract
This paper reviews field data where high-frequency torsional oscillation (HFTO) was seen on previous bit runs and hypothesizes on features or design metrics that may have directly influenced this vibration. This paper investigates four metrics of bit design: Cutter wear, shear length:shear area ratio, choice of secondary cutter material, and effective backrake. Hypotheses are established linking these metrics to HFTO, and then data from field runs is shown to correlate the hypotheses. At this point, a bit was designed and manufactured to put the HFTO avoidance hypotheses into practice. Prior to laboratory testing, a theoretical model is used to identify resonant torsional frequencies. A series of laboratory experiments followed to test the hypotheses and demonstrated that there is correlation between all factors, but in one case is counter to the hypothesis.
This information is of use when selecting or designing bits in environments where HFTO is known to occur. The findings may also assist in explaining performance that's below expectations where HFTO is not able to be explicitly measured.
Well Interference Detection from Long-Term Pressure Data Using Machine Learning and Multiresolution Analysis
Authors: Orta Aleman Dante , Horne Roland 
Published: September 2021

Abstract
Knowledge of reservoir heterogeneity and connectivity is fundamental for reservoir management. Methods such as interference tests or tracers have been developed to obtain that knowledge from dynamic data. However, detecting well connectivity using interference tests requires long periods of time with a stable reservoir pressure and constant flow-rate conditions. Conversely, the long duration and high frequency of well production data have high value for detecting connectivity if noise, abrupt changes in flow-rate and missing data are dealt with. In this work, a methodology to detect interference from longterm pressure and flow-rate data was developed using multiresolution analysis in combination with machine learning algorithms. The methodology presents high accuracy and robustness to noise while requiring little to no data preprocessing.
The methodology builds on previous work using the Maximal Overlap Wavelet Transform (MODWT) to analyze long-term pressure data. The new approach uses the ability of the MODWT to capture, synthesize and discriminate the relevant reservoir response for each individual well at different time scales while still honoring the relevant flow-physics. By first applying the MODWT to the flow rate history, a machine learning algorithm was used to estimate the pressure response of each well as it would be in isolation. Interference can be detected by comparing the output of the machine learning model with the unprocessed pressure data.
A set of machine learning, and deep learning algorithms were tested including Kernel Ridge Regression, Lasso Regression and Recurrent Neural Networks. The machine learning models were able to detect interference at different distances even with the presence of high noise and missing data. The results were validated by comparing the machine learning output with the theoretical pressure response of wells in isolation. Additionally, it was proved that applying the MODWT multiresolution analysis to pressure and flow-rate data creates a set of "virtual wells" that still follow the diffusion equation and allow for a simplified analysis.
By using production data, the proposed methodology allows for the detection of interference effects without the need of a stabilized pressure field. This allows for a significant cost reduction and no operational overhead because the detection does not require well shut-ins and it can be done regardless of operation opportunities or project objectives. Additionally, the long-term nature of production data can detect connectivity even at long distances even in the presence of noise and incomplete data.
Evaluation of Machine Learning Methodologies Using Simple Physics Based Conceptual Models for Flow in Porous Media
Authors: Magzymov Daulet , Ratnakar Ram R. , Dindoruk Birol , Johns Russell T. 
Published: September 2021

Abstract
Machine learning (ML) techniques have drawn much attention in the engineering community due to recent advances in computational techniques and an enabling environment. However, often they are treated as black-box tools, which should be examined for their robustness and range of validity/applicability. This research presents an evaluation of their application to flow/transport in porous media, where exact solutions (obtained from physics-based models) are used to train ML algorithms to establish when and how these ML algorithms fail to predict the first order flow-physics. Exact solutions are used so as not to introduce artifacts from the numerical solutions.
To test, validate, and predict the physics of flow in porous media using ML algorithms, one needs a reliable set of data that may not be readily available and/or the data might not be in suitable form (i.e. incomplete/missing reporting, metadata, or other relevant peripheral information). To overcome this, we first generate structured datasets for flow in porous media using simple representative building blocks of flow physics such as Buckley-Leverett, convection-dispersion equations, and viscous fingering. Then, the outcomes from those equations are fed into ML algorithms to examine their robustness and predictive strength of the key features, such as breakthrough time, and saturation and component profiles. In this research, we show that a physics-informed ML algorithm can capture the physical behavior and effects of various physical parameters (even when shocks and sharp gradients are present). Further the ML approach can be utilized to solve inverse problems to estimate physical parameters.
Low Adsorbing CO2 Soluble Surfactants for Commercially Viable Implementation of CO2 Foam EOR Technology
Authors: Katiyar Amit , Knight Troy , Grzesiak Adam , Rozowski Pete , Nguyen Quoc 
Published: September 2021

Abstract
Several gas Enhanced Oil Recovery (EOR) pilots enhanced with aqueous-foam based conformance solutions have been implemented in the last 30 years. While these pilots were technically successful, there were economic challenges limiting their commercial viability. Many of these pilots were implemented with water-soluble foaming surfactants that can get adversely affected by near wellbore gas-water gravity segregation and adsorption loss up to 90% of the injected surfactant. Novel, gas-soluble surfactants can be injected with the gas phase where these surfactants are carried with the gas to thief zones faster and deeper with relatively lower adsorption to the rock surface. However, the conventional foam modeling approach relied only on the surfactant concentration in brine to determine foam strength, which adversely predicted the performance of gas soluble surfactants. With proven laboratory evaluations and multiple successful field implementations, the advantages of low adsorbing and gas soluble surfactants cannot be ignored. In this paper, the advantages of surfactant partitioning to the gas phase are confirmed by correcting the conventional foam modeling approach while simulating 1D transport of CO2-foam displacing brine in porous media.
An empirical foam model was developed from the lab scale core flooding work of CO2foam transport through porous media using a novel gas-soluble foaming surfactant. While investigating the performance of gas soluble surfactants, global surfactant concentration was used to determine foam strength as the surfactant can transport to the gas-water interface from both the phases. Lab experiments and simulations with an improved foam modeling approach confirmed that a higher gas phase partitioning surfactant generated robust foam and deeper foam propagation while injecting surfactant with CO2in a water saturated core. In addition, comparing three partition coefficient scenarios around 1 on mass basis, the higher gas phase partitioning surfactant showed the larger delay in gas breakthrough. Overall, the simulation results with our better modeling approach do support the advantages of the higher gas phase surfactant partitioning in deeper foam transport and conformance enhancement for the gas-EOR technology.
An Integrated Workflow for Reserves Evaluation in the U.S. Permian Basin Based on SPEE Monograph 3
Authors: Xia Xiaoyang , Nelson Eric , Olds Dan , Connor Larry , Zhang He 
Published: September 2021

Abstract
In 2011, the Society of Petroleum Evaluation Engineers (SPEE) published Monograph 3 as an industry guideline for reserves evaluation of unconventionals, especially for probabilistic approaches. This paper illustrates the workflow recommended by Monograph 3. The authors also point out some dilemmas one may encounter when applying the guidelines. Finally, the authors suggest remedies to mitigate limitations and improve the utility of the approach.
This case study includes about 300 producing shale wells in the Permian Basin. Referring to Monograph 3, analogous wells were identified based on location, geology, drilling-and-completion (D&C) technology; Technically Recoverable Resources (TRRs) of these analogous wells were then evaluated by Decline Curve Analysis (DCA). Next, five type-wells were developed with different statistical characteristics. Lastly, a number of drilling opportunities were identified and, consequently, a Monte Carlo simulation was conducted to develop a statistical distribution for undeveloped locations in each type-well area.
The authors demonstrated the use of probit plots and demonstrated the binning strategy, which could best represent the study area. The authors tuned the binning strategy based on multiple yardsticks, including median values of normalized TRRs per lateral length, slopes of the distribution lines in lognormal plots, ratios of P10 over P90, and well counts in each type-well category in addition to other variables. The binning trials were based on different geographic areas, producing reservoirs, and operators, and included the relatively new concept of a "learning curve" introduced by the Society of Petroleum Engineers (SPE) 2018 Petroleum Resources Management System (PRMS). To the best of the authors’ knowledge, this paper represents the first published case study to factor in the "learning curves" method. This paper automated the illustrated workflow through coded database queries or manipulation, which resulted in high efficiencies for multiple trials on binning strategy. The demonstrated case study illustrates valid decision-making processes based on data analytics. The case study further identifies methods to eliminate bias, and present independent objective reserves evaluations. Most of the challenges and situations herein are not fully addressed in Monograph 3 and are not documented in the regulations of the U.S. Security and Exchange Commission (SEC) or in the PRMS guidelines. While there may be differing approaches, and some analysts may prefer alternate methods, the authors believe that the items presented herein will benefit many who are starting to incorporate Monograph 3 in their work process. The authors hope that this paper will encourage additional discussion in our industry.
New and Improved Single-Aqueous-Phase Retarded Acid SAPRA - Performance, Pore Volume Break through, and Wormhole Characterization
Authors: Wu Jing , Monette Matthew , Sickorez Jeff , Street Joseph , Tonmukayakul Peng , Lee Jesse , Craig Steven , Nguyen Quoc , Craig Steven 
Published: September 2021

Abstract
Controlling the reactivity of HCl is the most viable approach to successfully stimulate a high-temperature carbonate reservoir. It is essential to retard the HCl-carbonate rock reaction to achieve the optimum balance between total fluid used and enhancing well production. However, drawbacks intrinsic to the technology architectures have prevented the industry-wide adoption of these inventions. For instance, the conventional emulsified acid is well documented to exhibit high friction pressure, is cumbersome to prepare, and performance is sensitive to a multitude of parameters. The recently developed singleaqueous-phase retarded acid (SAPRA) represents one big step toward the right direction, but there is certainly ample room for improvement. This paper presents the next generation of SAPRA system and its laboratory findings. In this system, the HCl reactivity is regulated and retarded by a single, potent low-dosage additive, which is compatible with selected acid corrosion inhibitors, non-emulsifiers, H2S scavengers, and other commonly used additives, and if necessary, friction reducers as well.
Parameter Evaluations for Vertical Wells with Hydraulic Fracture Using Well-Testing and Deep Learning Method
Authors: Chen Zhiming , Dong Peng , Meng Meiling , Wang Jianan , Wang Tianyi , Li Dexuan 
Published: September 2021

Abstract
The reliability of well-testing interpretation largely depends on the experience of reservoir engineers, which make the issue of non-unique solution serious and increase its application threshold. Virtually, deep learning assistive techniques are good strategies in well-testing interpretation. Although some work has been done based on automatic interpretation techniques, there is still a lack of an automatic interpretation model with wide applicability and fast interpretation on parameter evaluation of vertically fractured well.
To improve this situation and make the well-testing interpretation easier to apply, this paper uses deep learning methods to build an automatic interpretation model of well-testing data for vertically fractured well. The model can automatically identify the corresponding parameters. The results in the validation set show that the median relative error of the curve parameter inversion is less than 10%. In addition, the accuracy of parameter prediction can be improved by increasing the weight of some important parameters in deep learning model training, such as permeability and fracture half-length. Finally, the automatic interpretation model is tested on a field case. The test results prove that the model has high accuracy and interpretation speed.
Novel Completion Designs in Horizontal Well with Transverse Hydraulic Fractures for Enhanced Recovery in Unconventional or Tight Reservoirs
Authors: Mishra Shubham , Fredd Christopher , Wilberg Dean , Yanbollu Umur 
Published: September 2021

Abstract
Low recovery, 2 to 15%, in unconventional plays (including tight reservoirs and source rocks) has long been recognized as a business deterrent. The industry applies enhanced oil recovery (EOR) techniques, along with hydraulic fractures in tight/unconventional plays, to improve the recovery. To maximize matrix sweep, the fractures are aligned in a face-to-face assembly. Such an arrangement can be achieved using vertical or longitudinal hydraulic fracture on horizontal wells, but these, generally, do not provide as effective reservoir contact (hydraulic fracture surface area) as horizontal wells with multistage transverse hydraulic fractures. The multistage transverse hydraulic fracture, however, comes at the costs of conformance issues with early water breakthrough from short-circuiting and inability to achieve fracture face-to-fracture face alignment of the injection and production fractures. The vast majority of wells drilled in unconventional plays are in the transverse configuration; hence, there is a need for an optimal solution for transverse fractures combined with improved oil recovery (IOR)/EOR approaches.
In this work, we introduce the multistage enhanced recovery (MS-ER) techniques that enable face-to-face alignment for optimal enhanced hydrocarbon recovery/IOR/EOR in horizontal wells with multistage transverse fractures, thereby enabling optimal recovery and mitigating the key risk of fracture short-circuiting.