bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling Gas Migration During a Gas Kick
Authors: Zankawi Ali , Sgher Mohamed El , Aminian Kashy , Ameri Samuel 
Published: April 2022

Abstract
Gas kick is an undesirable problem in the drilling process, which can potentially lead to a blowout. The primary intent of this study is to highlight gas migration and its effect on gas kick mitigation approaches that would benefit the drilling process. The integrated analysis provides valuable insight regarding parameters promoting efficient drilling processes, minimizing the risk of gas kicks. This study aimed to investigate the impact of critical parameters on gas migration during the gas kick in both water-based mud and oil-based mud and to promote an understanding of the dynamics of choke pressure, gas velocity, and bottomhole pressure based on completion and reservoir parameters.
This study reveals various factors affecting gas migration during gas kicks, characterized by different interactive parameters. These parameters include wellbore configuration, mud density, kick volume, drill-pipe size, reservoir temperature, and oil-water ratios. A commercial multiphase dynamic well control simulator was used in this study to develop two base models: Oil-Based mud (OBM) and Water-Based mud (WBM). The models were used to perform several parametric studies to investigate the impact of critical parameters on gas migration during the gas kick. Each type of mud acted differently and affected the gas migration discussed in this study. The study explicitly illustrates the different outcomes for each model during gas migration.
The parameters that range from most effective to least effective on gas migration are wellbore configuration, kick volume, drill-pipe size, mud density, and reservoir temperature in WBM, while in the OBM, the parameters that range from most effective to least effective are wellbore configuration, kick volume, drill-pipe size, oil-water ratio, mud density, and reservoir temperature. However, the main differences are the gas rise velocity and time in the base models. In water-based mud, the gas velocity is 97.8 ft/min, while the gas velocity in oil-based mud is 75.6 ft/min. The gas is discharged from the well within 48.2 minutes in the water-based mud, while the oil-based mud takes 115.7 minutes.
The Correlations of the Unconventional Reservoirs Properties and the Huff-n-Puff Gas EOR Potential Performance
Authors: Junira Adi , Ganjdanesh Reza , Williams Ryan , Nohavitza Jack , Sepehrnoori Kamy , Yu Wei 
Published: April 2022

Abstract
Cyclic (huff-n-puff) gas injection as a method of increasing oil recovery from unconventional reservoirs with low permeability has shown sufficiently positive results to justify its implementation in a number of fields. Nonetheless, not all of such injection results in encouraging results. Some field implementations of huff-n-puff results in marginal oil recovery increase from that of primary production case. The characteristics of an unconventional reservoir may have something to do with the appropriate choice of injection gas for use in that reservoir. For instance, a reservoir with oil that is low in heavy components (C7+) from molar fraction standpoint might not a proper candidate for a huff-n-puff field gas injection. In other words, for such type of injection gas to perform well in increasing oil recovery, the in situ oil should have a certain level of C7+ molar fraction. This study aims at finding out what types of gas are the proper choices for huff-n-puff injection gases in unconventional reservoirs with specific characteristics. In a sense, it can be considered as an attempt to create a kind of screening criteria related to the injection gas suitable for huff-n-puff EOR in such an unconventional reservoir. In achieving that, a number of models which are based on real field data of a number of producing oil fields in continental United States are used in numerical simulations. The analysis on the results provided insights on the proper injection gas selections as tabulated in this writing.
Integrating the Energy Transition into Petroleum Engineering and Geoscience Education
Authors: Ershaghi Iraj , Paul Donald L. 
Published: April 2022

Abstract
The emerging carbon-constrained environment for energy is creating both opportunities and challenges for the established oil and gas industry. The engineering and geoscience professionals in this Industry need to meet both the challenges of the Energy Transition and continue to provide the feedstock for hydrocarbon-based products needed for a stable and robust economy. While the fossil fuel in general includes coal, decoupling petroleum from coal and replacing coal with natural gas can offer substantial carbon emission reductions to the power sector and growth opportunities for the petroleum industry. The Energy Transition can also create new opportunities for the petroleum engineering schools and geoscience programs to develop and offer expanded educational opportunities for both new graduates and industry professionals to equip them with critical expertise and leadership skills for careers in the low-carbon energy future.
A Robust Machine Learning Model to Predict the Relative Permeability of an Oil Porous Medium at Elevated Temperatures
Authors: Kumar Saket , Gautam Sandarbh , Varun Rit , Khan Murtaza Ahmed 
Published: April 2022

Abstract
Thermal Enhanced Oil Recovery (TEOR) such as SAGD, CSS and other steam injection processes have been employed in heavy oil reservoirs of North-American and Middle-East countries for oil recovery. Elevation of temperature during this process leads to wettability alteration, IFT variation, viscosity reduction, asphaltene and resin precipitation. These variations during TEOR impact relative permeability to each fluid phase in the reservoirs. Therefore, available models like the Corey model and Stone's model for estimating the relative permeability cannot be directly used for reservoir simulation/modelling study of such reservoir where TEOR is implemented. Hence, an attempt has been made to develop a reliable, accurate, and robust data-driven model for two-phase oil/water relative permeability using the XG-Boost machine learning algorithm which accounts for the temperature's effect.
For this study, numerous sets of oil and relative permeability data have been sourced, compiled and validated using our proposed model via the supervised XG-Boost approach. For model construction, 1270 oil relative permeability and 1230 water relative permeability data points were obtained from literature covering different rock/fluid and reservoir conditions. This study presents a new data-driven model developed using the XG-Boost algorithm to predict two-phase oil/water relative permeability over a wide range of temperatures in unconsolidated sand and sandstone formations. Moreover, the proposed model gave us better results based on the statistical error analysis.
Geological Aspects of Using Saline Aquifers in the San Joaquin Basin for Storage of Compressed Air or Carbon Dioxide
Authors: Davis Mathew , Ershaghi Iraj 
Published: April 2022

Abstract
A question in the minds of many is the potential use of saline aquifers in California for storing compressed air and for CO2 storage. This paper is the result of an extensive study on the geological properties of subsurface saline water containing geologic layers located below the freshwater limits in the San Joaquin Valley (SJV) of California. There are many thousands of pass-through wells drilled for hydrocarbon extraction in the area that can provide subsurface information on the saline aquifers. We discuss some of the saline aquifer properties and geologic aspects associated with the subsurface storage of compressed air and or carbon dioxide.
The raw database to generate the information included archives of CalGEM with respect to the existing and previously drilled oil and gas wells in the SJV Basin as well as separate studies by the USGS, Kang (2016), and Gillespi (2017). We mapped these aquifers across the valley and estimated ranges of pore volumes, the deliverability and the injectivity range for storage purposes. We also studied the sealing characteristics of these sands with respect to over and under burden and the geologic faulting in the San Joaquin Basin. We studied the drilling reports of many key wells and identified the lithologies of interest and examined relevant petrophysical properties. Estimates of capacity and deliverability were generated for these intervals. The legal ownership issues of operating these saline aquifers as storage were not part of this study.
Our critical observations include aspects of salinity, petrophysical properties, and the areal extent. Knowing the salt content of in-situ water is essential for site selection and the economics of repurposing idle wells to connect to these aquifers. The base of drinkable water (USDWs) (&lt;10,000 mg/L) deepens northwest to southeast over the San Joaquin Basin, likely due to significant freshwater recharge from the Sierra Nevada Mountains. In the northwestern portion of Kern County, a number of wells intersect waters with 3000 and 10,000 ppm above 2000 ft TVD, within the Tulare Formation. At North Belridge field, a salinity reversal is apparent below 6900 ft., and salinities for zones below 7200 ft. range from 10,000 to 32,000 ppm (Gillespi, 2019). From the maps and correlative sections that relate to the areal extent of the target saltwater sands, we estimated the range of storage volumes, injectivity, and deliverability capacities for various wet sands.
The information generated and included in the paper is a reference point for the operators in the SJV, CA. It can help with the site selection for potentially converting some or all existing idle wells that are on the verge of abandonment and repurposing the wells for energy storage and for subsurface CO2 and other waste disposal purposes using the shallow saline aquifers.
A Generalized Dynamic Transfer Function for Ultra-Tight Dual-Porosity Systems
Authors: Zhang Jingzhe , Raslan Mohammed , Wu Cheng , Jessen Kristian 
Published: April 2022

Abstract
The Warren and Root (1963) transfer function laid the foundation for describing the mass transfer between the matrix and fracture blocks in dual-porosity (DP) reservoir simulation. However, the pseudo steady-state (PSS) assumption imbedded in the approach of Warren and Root is no longer applicable when the duration of the transient state is prominent (tight oil or shale gas reservoirs). Lim and Aziz (1995) derived new shape factors in a framework that avoids the PSS assumption. However, similar to the formulation of Warren and Root, the approximation of Lim and Aziz fails to capture the pressure gradients inside matrix blocks for tight rocks with substantial characteristic times for mass transfer.
In this paper, we introduce a generalized dynamic transfer function that can accurately predict the pressure response of ultra-tight DP formations. Based on the Vermeulen (1953) approximate solution, we first derive the new transfer function to model fluid flow for one, two, and three sets of perpendicular fractures where the matrix blocks are approximated by planar, cylindrical, and spherical geometries, respectively. Then, we apply it for rocks with anisotropic permeability. We extend our transfer function to represent more realistic geology by considering irregular-shaped matrix blocks. The proposed transfer function accounts for physical mechanisms at play in the reservoir and is applicable to describe different diffusion-type processes.
Development and testing of the dynamic transfer function were done in the open-source environment of the MATLAB Reservoir Simulation Toolbox (MRST). The implementation was validated using single-block DP calculations and fine grid single-porosity (SP) models. We report results from several examples covering a broad range of reservoir parameters. For comparison purposes, we also report the simulation results from a traditional transfer function, incorporating Lim and Aziz shape factors, in MRST and commercial simulators (CMG and ECLIPSE). We demonstrate that our proposed dynamic transfer function accurately predicts the pressure response across early and late times, while the traditional transfer function with Lim and Aziz shape factors can depart substantially from the true solution for ultra-tight DP reservoirs.
A Comprehensive Review of Tracer Test Applications in Geothermal Reservoirs
Authors: Aydin Hakki , Nagabandi Nirup , Jamal Diyar , Temizel Cenk 
Published: April 2022

Abstract
Tracer test is a strong tool that is used to understand the connectivity between injection and production wells in geothermal reservoirs. It is essential to design and implement a tracer test for particular reservoir properties. Inappropriate tracer tests, might cuase wrong reservoir characterization interpretations. This study incorporates in the design, the implementation, and the interpretation of tracer tests in geothermal reservoirs. This study is populated with numerous field applications to ensure better understanding of the subject.
The study initially present the types of tracers used in geothermal reservoirs. The appropriate tracer type is selected based on various parameters such as reservoir conditions, economics, type of measurement devices available, minimum detection concentration, environmentally friendly, and stability at reservoir conditions. Once the type of tracer is selected, the amount of tracer to be injected and the tracer sampling frequency are determined based on the distance between wells, mean traveling time, and the desired peak concentration. The tracer is injected as slug/continuous type to the selected injection wells and sampling from production wells. The measured tracer concentrations are then modeled with analytical methods such as the multi-fractures, single fracture, dual-porosity, and homogenous models.
Naphthalene sulfonates, is frequently used in high-temperature geothermal reservoirs because of is high resistance and half-life in harsh conditions. Salts such as sodium chloride and potassium chloride are also conservative in harsh conditions; however, a large amount of salt is required to be injected to create an additional concentration in the reservoir brine, which already includes a certain salt concentration. Fluorescein is mostly applicable in low enthalpy reservoirs because of its weakness at high temperatures. Analytical models are matched with field data by using the nonlinear least square method. The most representative reservoir model is determined by evaluating the sum of the squared differences between tracer concentrations of the model and field data. Geothermal reservoirs are generally best matched with multi-fractures and dual-porosity models because of the secondary permeability and porosity of tectonic activities and mineral dissolution mechanisms.
This study, provides a detailed information about tracer test design, implementation, and interpretation. It serves as a guidance by including numerous field cases and the latest research about tracers in geothermal.
Experimental Investigation of Foam Flooding Performance in Bulk and Porous Media for Carbonates Under Harsh Conditions
Authors: Xiong Ding , Ahmed Shehzad , Alameri Waleed , Al-Shalabi Emad W. 
Published: April 2022

Abstract
Foam injection has been promoted as a reliable method for improving the sweep efficiency in heterogeneous carbonate reservoirs by modifying the properties of the injected gas and hence, providing mobility control effect. However, the conditions of the Middle Eastern carbonate reservoirs are quite detrimental to foam performance, leading to unoptimized mobility control. This challenge has motivated the improvement and development of different foaming agent formulations that can withstand the harsh conditions in carbonate reservoirs of high temperature and high salinity. In this study, the effect of different amphoteric and switchable surfactants on bulk foam performance were investigated and later the optimum formulation was evaluated in carbonate porous media for EOR under high salinity and temperature conditions. For this purpose, the solutions containing different commercial amphoteric and amine-based switchable surfactants were prepared in high salinity brine (20 wt%) at high temperature conditions (80 °C). Initial screening was performed by conducting series of foamability and foam stability tests at high temperature. Foam generation and endurance were also investigated in the presence of crude oil. Foam performance was evaluated in carbonate core samples under different foam qualities and at reservoir conditions. After selecting the optimal foam quality for effective foam generation, the oil recovery experiment was then performed to recover the remaining oil after secondary N2-gas flood.
The results from bulk foam experiments demonstrated the superior properties of betaine-based surfactant (B-1235), in which the highest foam generation and foam stability performance were achieved. Foam endurance of B-1235 was also found comparable to the foam produced by switchable diamine (DTTM) surfactant; however, DTTM surfactant showed poorer foamability performance. In the presence of crude oil, B-1235 surfactant was able to maintain the foam properties, compared to other tested surfactants. The optimum concentrations for B-1235 in the absence and presence of crude oil were found to be 0.25 wt% and 0.5 wt%, respectively. The injection of foam stabilized by the B-1235 was able to pronouncedly increase the mobility reduction factor (MRF) at all the tested foam qualities under high-pressure and high-temperature conditions. Coreflood investigations indicated an optimal foam quality at 70% for all tested surfactant concentrations. The cumulative oil recovery after foam injection was found to be 67%, including 25% tertiary incremental oil recovery by foam flooding. The overall performance of the tested betaine-based surfactant is promising as an effective mobility control during foam EOR process and promotes further application in difficult Middle Eastern carbonate reservoir conditions.
Framework for the Prediction and Assessment of Corrosion Damages in Amine Systems Using Plant Data, Process Simulation and Data Analysis
Authors: Galatro Daniela , Navas Gladys 
Published: April 2022

Abstract
The prediction and assessment of corrosion rates in amine gas treating units include reviewing current and historical environmental components such as amine type, H2S and CO2 loading, and temperature; to identify, trend, and provide corrective actions for potential problems related to streams quality, contamination, or damage diagnosis. This review is completed with data obtained from traditional off-line monitoring methods, such as mechanical integrity reports and analysis of the process streams, to capture the state of criticality of the system. Recent advances in corrosion modeling of amine systems allow integrating this data with numerical modeling to effectively quantity and predict corrosion rates. Numerical modeling is based on empirical models, which are usually limited within the ranges of data used in their development, unlike first-principles models that can accurately extrapolate beyond this range. Furthermore, empirical models may lead to significant errors when extrapolated outside the range of the training data. Therefore, their accuracy can be substantially improved by adding data generated from first- principles models through a sensitivity analysis of process and corrosion-related variables. This work proposes a framework for predicting and assessing corrosion rates in amine gas treating units, using surrogate models that combine process simulation software and plant data. A first-principles model of a simulated amine plant is employed to predict process-related variables, combined with a mechanistic model used to predict corrosion rates. Once the data is collected, exploratory data analysis is employed to quantify the correlation between process and corrosion variables, dimensionality reduction, outliers’ detection and treatment, and model performance evaluation. This framework also provides guidelines for selecting surrogate models predicting process variables and corrosion rates. These models can eventually be coupled with multi-objective optimization algorithms for control purposes.
Employing Regression Analysis to Demonstrate the Impact of Hyperbolic Decline Curve Parameters on Long-Term Production Forecast Accuracy for Unconventional Oil and Gas Production in the Bakken and Barnett
Authors: Younk Nathaniel , Hoffman B. Todd 
Published: April 2022

Abstract
Forecasting production from unconventional reservoirs is challenging because of the uncertainty that arises from intricate fracture networks, complex transport mechanisms, and convoluted flow configurations. The accuracy of decline curve analysis for such reservoirs has been questioned due to the limited amount of long-term production data available. That being so, some unconventional reservoirs, such as the Bakken and the Barnett, have produced for 15-20 years, providing an adequate amount of data to validate the accuracy of the hyperbolic decline curve method, shed light on proper parameters – b and Di, and determine the amount of production history necessary to trust regression techniques.
To test this, an extensive and versatile regression analysis model was built in Python using least squares optimization to match specific durations of production data – first 6 months, first year, first two years, etc. The model outputs the optimal parameters – b and Di –to match the specific duration. Additionally, fixed b values from 0.5 to 1.5 are tested where only Di is optimized through the model. To understand how accurately the models predict production, they are validated against the most recent 5 years of data, which was not included in the matching period. For a statistically significant sample size, around 700 wells in the Bakken and 1800 wells in the Barnett with start dates between 2005 and 2010 were used.
The results show that in order to have confidence in the model's ability to predict production, more than 3 years of production data must be available. If 3 years of data is not available, the hyperbolic exponent, b, should be set close to 1.0 for Bakken wells (and likely other unconventional liquid rich wells) and between 1.0 and 1.2 for Barnett wells (and likely other unconventional gas wells). Additionally, the initial nominal decline rate, Di, should be chosen in accordance with the hyperbolic exponent. Not only do these guidelines result in satisfactory, long-term predictions, but they mitigate any significant error influenced by the underlying relationships between b and Di. These curve-altering relationships induce both positive and negative impacts on the predictions. If b is improperly chosen, overestimation in late-life production profiles may ensue. Alternatively, if Di is improperly chosen, early-life production may be too high.
Since production forecasting is a necessity for a company to determine its present value, this paper provides knowledge and guidance regarding forecasting procedures and parameter settings for North American unconventional operators. Using decline curve analysis to accurately predict oil and gas rates is pertinent to the longevity of these unconventional reservoirs.