bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Experimental Study of Single Component Adsorption/Desorption Isotherms
Authors: Wolf Jeremy , Maaref Sepideh , Tutolo Benjamin , Kantzas Apostolos 
Published: March 2022

Abstract
Within tight reservoirs, gas is stored both as free gas contained in the pores and adsorbed gas on the rock matrix. Adsorbed gas exhibits liquid-like densities resulting in significantly more gas being stored on the rock surface. By having accurate adsorption/desorption data of injected and reservoir gases, one can acquire a better understanding of the true original gas in place, as well as how to maximize production through optimal enhanced gas recovery (EGR) techniques.
The aim of this research is to measure the adsorption/desorption isotherms of single-component gases on activated carbon in a series of pressure steps up to 1500 psi. The experiments are conducted at varying temperatures to establish a wide array of isotherms. Temperatures are maintained through the use of a water bath. The obtained isothermal pressure data is modeled using the Gibbs sorption isotherm and the Langmuir mathematical model, the most popular and simplistic approach. Furthermore, by plotting pressure divided by adsorption capacity as a function of pressure, Langmuir parameters are determined.
From the experiments, isothermal pressure data was able to be modeled using the Gibbs sorption isotherm and the Langmuir isotherm and Langmuir parameters were determined and compared. It was observed that decreasing temperature and increasing hydrocarbon molecular weight were the main contributing factors to higher sorption capacities of the single component gases. It is important to quantify both adsorption and desorption processes because in EGR techniques such as cyclic solvent injection (CSI) injected gas is competitively adsorbing onto the rock, causing the adsorbed reservoir gas to be displaced, desorb, and subsequently be produced. Due to the aforementioned irreversibilities, by using adsorption metrics to quantify the amount of gas desorbed within the reservoir, gas production may be overestimated.
To date, most adsorption/desorption experimental work has been conducted on methane, carbon dioxide, and nitrogen. This research aims to expand on previous literature by performing adsorption/desorption experiments on higher chain hydrocarbons, such as ethane and propane. By doing so, CSI EGR schemes can be more meticulously modeled as the inclusion of higher chain hydrocarbons allows for the model sorption inputs to be more representative of typical unconventional reservoir gas. This in turn will allow for more accurate production forecasting, helping minimize the financial risk of costly EGR projects.
Mitigating Surge and Swab by Changing Tripping from a Batch to a Continuous Process
Authors: Pilgrim Rick , Butt Stephen 
Published: March 2022

ABSTRACT
A significant portion of the time required to drill an oilwell is spent moving the drillpipe in or out of the wellbore, called "Tripping". The drill crew must trip pipe for numerous reasons. These include changing the bit as it wears out, inserting new casing strings, cleaning and treating the drillpipe and/or wellbore to allow more efficient drilling, and to run in various tools that perform specific jobs required at certain times in the oilwell construction plan.
The traditional tripping process (TTP) inherently creates pressure transients developed from stopping and starting the vertical motion of the drillpipe during connections. These pressure transients called, "Swapping" and "Surging", contribute to borehole instability, restrict tripping speed, and increase non-productive time (NPT). This paper focuses on the benefits that can be gained from a bottom hole pressure (BHP) surge/swab perspective. Specifically, how these undesirable pressure transients can be dramatically reduced by modifying the TTP from a start/stop (batch) process to a continuous tripping process (CTP), where drillpipe tripping speed is kept constant throughout the entire tripping sequence and thereby significantly reducing the numerous starts and stops associated with traditional tripping.
In this paper both the TTP and CTP systems were kinematically modeled using a custom simulator coded in C#. It is important to note that all the equipment used in the modified CTP exists and has only been reconfigured to facilitate a continuous process. This is inclusive of real-life limits for such items as derrick height, traveling block (TB) height as well as velocity, acceleration and inertia limits for TB, crown blocks, drawworks, their associated reeving configurations as well as racking system arms, grippers, and latches.
The simulation results indicates that for a continuous tripping system we can achieve a ~73% slower average pipe speed that has an overall tripping speed approximately 4 times faster than traditional tripping. CTP decreased BHP deviation significantly. The continuous tripping process was awarded a patent by USTPO in 2016, US 9,441.247 B2.
Child/Parent Well Interactions; Study the Solutions to Prevent Frac-Hits
Authors: Haghighat Alireza , Ewert James 
Published: March 2022

Abstract
Maximizing the hydrocarbon recovery for a given unconventional asset often clashes well spacing considerations against completion design. This can result in complex child/parent well interactions that can include frac-hits and reserve reallocation. In planning for a successful field development within the vicinity of producing assets, the risk of frac-hits must be evaluated carefully to minimize any damage and potential profit loss.
Multiple factors such as depletion, well spacing, rock properties, and completion design all contribute to the risk of a frac-hit. Understanding the probable cause of a frac-hit allows for appropriate mitigation operations such as parent well pre-loading, re-fracturing, increased offset spacing, and revised completion design to be considered. To evaluate each remedial operation, several unconventional Permian oil wells were studied with Rate Transient Analysis (RTA) to identify well and reservoir characteristics. Based on these results multi-phase/multi-well numerical modeling was performed to evaluate how effective each operation would be to minimize the risk of future frac-hits.
Simulation results regarding pressure and production performance of parent/child wells will be presented applying different frac-hit mitigation methods. Pressure build-ups around the wellbore were determined considering parent well shut-in; gas injection and water injection (pre-loading). Water injection resulted in the highest pressure build-ups in the vicinity of the wellbore (which reduces the risk of a frac-hit); however, it takes several months to unload the injected water. Production uplift due to a re-fracturing operation was evaluated with numerical modeling assuming different fracture designs that include the extension of current hydraulic fractures and adding new fractures. The performance of child and parent wells were then investigated by changing the well spacing and completion. Optimum combinations of well spacing and completion designs were determined to maximize child/parent well production and minimize the risk of frac-hits. Finally, the impact of parent well depletion on the productivity of the child well is determined.
This work presents a replicable and accessible workflow to assess the impact of multiple frac-hit mitigation methods on reservoir performance.
Characterization of Dynamic Wormhole Growth and Propagation During CHOPS Processes by Integrating Rate Transient Analysis and Pressure-Gradient-Based Sand Failure Criterion
Authors: Jiang Liwu , Liu Jinju , Liu Tongjing , Yang Daoyong 
Published: March 2022

AbstractIn this work, theoretical models have been formulated, validated, and applied to characterize the dynamic wormhole growth and propagation dynamics during CHOPS processes by integrating rate transient analysis (RTA) and a pressure-gradient-based (PGB) sand failure criterion. More specifically, a coupling fluid-solid flow model is proposed by incorporating the recently proposed PGB sand failure criterion with sand production. Then, the source function method is applied to solve the fluid flow problem in the matrix subsystem by considering each generated wormhole segment as a sink source, while the finite difference method is applied to solve the fluid-sand flow problem in the wormhole subsystem. The sand failing at each segment is induced and propagated once the PGB sand failure criterion has been reached. Furthermore, transient rate type curves are generated to determine the dynamic wormhole network conditioned to the measured fluids and sand production profiles. Also, effects of the PGB sand failure criterion and reservoir properties on the transient rate behaviour for CHOPS wells can be examined and analyzed. A gradual increase in the production rate profile occurs at the early times due to the wormhole growth and propagation. The wormhole network can be dynamically characterized by matching both the sand production rate and transient fluid production rate. The former is found to be greatly affected by the breakdown pressure gradient, while the effective wormhole coverage and intensity dominate the latter. Once the pressure responses on a static wormhole network are validated with numerical simulation, the newly proposed method has been extended to field applications under various constraints, demonstrating that the fluid and sand production data of CHOPS wells can be integrated to accurately characterize the dynamic wormhole network within a unified, consistent, and efficient framework.
A CPP Model to Asphaltene Precipitation; Mapping p-p Interactions onto an Equation of State
Authors: Alimohammadi Sepideh , James Lesley , Zendehboudi Sohrab 
Published: March 2022

AbstractAsphaltene may destabilize during the oil recovery, transportation, and processing and cause significant flow assurance problems that negatively affect the operational expenditures (OPEX). Modeling investigation of asphaltene precipitation and consequently deposition is a vital research component in flow assurance requiring the accurate description of the phenomena under various operational conditions. The structure of asphaltene molecules and the presence of heteroatoms play a significant role in the intermolecular forces and the mechanism of asphaltene aggregation. Nevertheless, the intermolecular forces, e.g., polar forces, and their addition to thermodynamic modeling of asphaltene phase behavior still need investigation. While the traditional equation of state (EoS), e.g., cubic EoS, does not provide any special treatment to polar energy, the π-π interaction and polar effect can be mapped into the EoS using a separate polar term. In this research, we use cubic EoS, cubic plus polar (CPP) EoS, and molecular dynamics (MD) (three different modeling approaches) to analyze the effect of asphaltene structure and operational conditions on the precipitation phenomenon. Comparing the error associated with correlation and prediction results of the models, we show that the CPP approach using optimization to tune parameters of the EoS is the most reliable approach, followed by CPP EoS using MD to find dipole moment for the aryl-linked core asphaltene structure. The CPP EoS and MD optimizing island structure for asphaltene is the third-best model, and SRK EoS is a less efficient approach. Considering the values for dipole moment and molecular weight of asphaltene, along with correlation and prediction ability of the techniques, it is revealed that polar forces can be considered in a separate term in addition to van der Waals force to increase the model efficiency. Moreover, the aryl structure with a 750 g/mol molecular weight and one/two thiophene/pyridine group is the most proper asphaltene structure.
Using the FMB Model to Determine Which Wells Out of a Group of Wells Belong to the Same Common Pool
Authors: Tabatabaie S. Hamed , Behmanesh Hamid , Mattar Louis 
Published: March 2022

Abstract
In order to properly conduct material balance calculations, the wells must be producing from the same reservoir. Identification and grouping of wells in a common reservoir can be a challenging task.
The Flowing Material Balance Model (FMB model) was developed. It utilizes a well’s flow rate and flowing pressure history to identify which wells belong in the same reservoir, and which do not. This FMB Model continuously converts the flowing pressures and rates of each well into the average reservoir pressure. If these average reservoir pressure trends overlap, it indicates that the wells are in the same reservoir. If any of the trends are different, then those wells belong to different reservoirs.
The average reservoir pressure is determined in two ways. The first is from the productivity index and the flowing rates and pressures of that well. The second is from the material balance equation for the total production of the group of wells. These two average reservoir pressure trends will track over time if the well grouping is properly defined (i.e. all the wells in that grouping belong to the same reservoir), and if the correct hydrocarbon-in-place is used.
The FMB Model can additionally be used to history-match the flowing pressure of each well (using the flow rate as a control) or to match the flow rate of each well (using the flowing pressure as a control). These visual history matches increase our confidence in the interpretation of the flowing material balance, and can be used to investigate the sensitivity of magnitude of the hydrocarbons-in-place
One field study consisting of three adjacent gas wells, coming on production at different times, and some of the wells not having a reliable initial pressure, illustrates clearly which wells are in the same reservoir and which ones are not, and yields the correct values of original-gas-in-place.
Deconvolution Overcomes the Limitations of Rate Normalization and Material Balance Time in Rate-Transient Analysis of Unconventional Reservoirs
Authors: Ruiz Maraggi Leopoldo M. , Lake Larry W. , Walsh Mark P. 
Published: March 2022

Abstract
Rate-transient analysis (RTA) is routinely used for unconventional production data analysis and forecasting. RTA uses rate normalization along with material balance time to estimate:(a) flow regimes, (b) the time of end of transient flow, and (c) the drainage volume and to thereby predict the estimated ultimate recovery (EUR) of wells. However, rate normalization approximates deconvolution, and material balance time is only strictly applicable for constant-pressure or constant-rate systems. This work investigates the validity of rate normalization and material balance time for synthetic and tight-oil well examples producing under variable bottomhole flowing pressure (BHP) conditions.
This work generates synthetic examples with different BHP histories and uses deconvolution to estimate a constant-pressure rate/material balance time response. First, we plot and compare the normalized rate vs. material balance time, the deconvolved rate/material balance time and the unit-pressure-drop rate vs. constant-pressure material balance time. The latter plot represents the constant-pressure solution of the 1D flow of a slightly compressible fluid (reference case). Second, we evaluate the plots of material balance time vs. time, deconvolved material balance time vs. time and constant-pressure material balance time vs. time. Third, we fit the reference type curve to a plot of the normalized rate vs. material balance time and the deconvolved rate vs. deconvolved material balance time to determine the reservoir properties to then estimate the EUR using time superposition. We conclude by illustrating the application of these steps to tight-oil wells in which we use deconvolution to estimate the unit-pressure-drop rate and the constant-pressure material balance time.
The results of this study are the following. First, BHP changes alter the slope of the log-log normalized rate-vs. material balance time plot. Second, BHP variations introduce error to the behavior of the material balance time vs. time function leading to incorrect estimates of the time of end of transient flow. Consequently, normalized-pressure rate and material balance time are not always reliable variables to properly identify the flow regime(s) and thus, to correctly estimate the time of end of transient flow and EUR. Alternatively, applying deconvolution to rigorously account for the pressure variations and generate the unit-pressure-drop rate and the constant-pressure material balance time solves these problems.
This paper investigates the validity of rate normalization and material balance time in RTA of unconventional reservoirs. Caution is needed when applying rate normalization and material balance time since these might lead to incorrect estimates of the time of end of transient flow and EUR. For this reason, deconvolution should be included as an integral part of the RTA workflow.
Rate-Pseudopressure Deconvolution Enhances Rate-Time Models Production History Matches and Forecasts of Shale Gas Wells
Authors: Ruiz Maraggi Leopoldo M. , Lake Larry W. , Walsh Mark P. 
Published: March 2022

Abstract
Physics-based and empirical rate-time models inherently assume constant bottomhole flowing pressure (BHP), an assumption that may not hold for many unconventional wells. Hence, applying these models without accounting for BHP variations might lead to inaccurate: (a) flow regime identification, (b) estimation of the parameters of these models, and (c) estimated ultimate recovery (EUR) and drainage volumes. This study evaluates and compares the predictions of rate-time relations including and ignoring corrections for time-varying BHP for both synthetic and shale gas wells.
We generate a real gas synthetic case with errors in the time-varying BHP. First, we convert pressures into pseudopressures. Second, we deconvolve the pseudopressure history by applying the regularized exponential basis function inverse scheme to obtain an equivalent rate—the unit-pseudopressure-drop rate at standard conditions—at constant BHP. Third, we history-match the production using the scaled single-phase compressible fluid physics-based model for three different approaches: (a) using rate-time-pressure data with rate-pseudopressure deconvolution, (b) using rate-time-pressure data using just rate-pressure deconvolution, and (c) using only rate-time data. Finally, we compare the results in terms of their history-matches and estimated reservoir parameters. We conclude by illustrating the application of this procedure to shale gas wells.
For the synthetic case, the fit of the single-phase compressible fluid rate-time model using rate-pseudopressure deconvolution can accurately estimate the original gas-in-place, characteristic time, gas permeability, and fracture half-length. In contrast, considerable errors are noted when either using rate-pressure deconvolution or failing to account for variable BHP. Regarding the shale gas examples, the rate-pseudopressure deconvolution scheme accurately identifies the flow regimes present in the well, which can be difficult to detect by only analyzing rate-time data. For this reason, the fits of the scaled single-phase compressible fluid model using only rate-time results in unreasonably large estimates of the reservoir parameters and EUR. In contrast, the application of rate-pseudopressure deconvolution constrains the fits of single-phase compressible fluid model yielding more realistic estimates of time of end of linear flow, and EUR.
This paper illustrates the application of a workflow that accounts for variable BHP by estimating an equivalent constant unit-pseudopressure-drop gas rate (at standard conditions). We illustrate the workflow for a particular decline-curve model, but the workflow is general and can be applied to any rate-time model. The approach history matches and forecasts the production of unconventional gas reservoirs using rate-time models more accurately than assuming constant BHP.
Using Machine Learning Method to Optimize Well Stimulation Design in Heterogeneous Naturally Fractured Tight Reservoirs
Authors: Liu Huifeng , Cui Longlian , Liu Zundou , Zhou Chuanyi , Yao Maotang , Ma Haoming , Liu Qi 
Published: March 2022

Abstract
The reservoirs in Kuqa foreland area of Tarim Basin in China are ultra-deep HTHP (High Temperature and High Pressure) naturally fractured sandstone reservoirs. Due to low permeability of the matrix (&lt;0.1mD), stimulation of the natural fractures is the key to well productivity enhancement. Different stimulation techniques with different stimulation strengths have been tried in the last decade, but stimulation effectiveness varied. Therefore, machine learning method is employed to identify the main controlling factors and optimize the well stimulation design.
Firstly, geological data, stimulation data, productivity data, etc. for more than 200 wells were used to develop data analysis models, and the major characteristic parameters and their weightiness were determined through machine learning. Afterwards, the stimulation parameters of these wells, including injection rate, fluid volume, proppant volume, etc., were correlated with post-stimulation open flow capacity increments using several regression modeling methods, and the weightiness of these stimulation parameters was determined through machine learning. Cross validation method was used to choose the most accurate and stable model, which was then used to optimize the stimulation parameters of new wells. The model is applied to two test wells. The stimulation technologies and stimulation parameters of the two wells are optimized. Compared with the natural productivity, the productivity after stimulation was increased by 5.5 times and 21.5 times respectively.
Machine learning algorithms are used to find an implicit rule from a large amount of data and express the rule with a high dimension nonlinear algorithm equation. It is very useful but seldom has applications in the area of reservoir stimulation. This paper found the controlling parameters of reservoir stimulation in Kuqa foreland area of Tarim Basin through machine learning and successfully used it in well productivity enhancement practices.
Critical Assessment of the Hybrid Impact of Surfactants on Modified Salinity Water Flooding
Authors: Belhaj Ahmed , Singh Navpreet , Sarma Hemanta 
Published: March 2022

AbstractIn recent years, interest in water-based EOR methods and the combination of modified seawater with chemicals has grown due to their economic improvement of oil production. The hybrid application of low salinity water with surfactants (LSS) flooding has a promising potential to significantly increase the oil recovery. LSS flooding, a novel hybrid EOR approach, has recently proven its capability of altering rock surface wettability and reducing oil-water IFT. In this study, we present a comprehensive assessment of the fundamentals and recent developments of LSS flooding, as well as lessons learned from previous studies and the key uncertainties associated with successful implementation. The study begins with an overview of surfactant flooding, low salinity water (LSW) flooding and the hybrid application of LSW flooding processes. The LSS flooding process in different reservoir types and the recovery mechanisms associated is then discussed. The recent laboratory studies for LSS flooding and the surfactant losses associated in porous media are also reviewed. Recent studies of LSS flooding have concluded the advantages of higher oil recovery, higher surfactant stability, lower surfactant retention, and lower chemical consumption compared to conventional surfactant flooding. Most of the LSS flooding application has been performed on sandstones with remarkable outcomes, meanwhile, it’s application in carbonates has garnered attention in recent years and some promising findings were reported. The efforts of this work can provide further understanding of the LSS flooding process and its underlying mechanisms, especially in carbonates which are not fully covered in the literature. Finally, this paper gives more insight into the potential success of LSS flooding over surfactant and LSW flooding processes.