bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sweep Improvement in CO2-IOR Through Direct CO2 Viscosification
Authors: Afra Salar , Firoozabadi Abbas 
Published: September 2022

Abstract
Modification of CO2 mobility to prevent premature breakthrough and poor sweep efficiency is a major step for improving oil recovery in CO2 injection. Water-alternating-CO2, foam, and direct viscosification are the main proposed methods to limit CO2 mobility and improve the sweep efficiency. CO2 direct viscosification is the most desirable option. Control of the process is very simple. In this work, an engineered molecule is introduced to increase CO2 viscosity and improve oil displacement efficiency in CO2 flooding as a secondary recovery technique.
An engineered oligomer of 1-decene (P1D) with the approximate molecular weight of 2950 g/mol is used to viscosify supercritical CO2. A mixture of 1.5 wt% P1D in supercritical CO2 with the relative viscosity of 5.2 at the temperature of 140 ˚F and pressure of 3500 displace the oil in most of our experiments. A set of coreflood experiments in sandstone and carbonate rock samples are carried out to evaluate and compare oil recovery performance by neat and thickened CO2. Hexadecane, with viscosity of 1.7 cp and density of 0.745 kg/m3, and a dead crude oil sample, with viscosity of 4.1 cp and density of 0.843 kg/m3, at the pressure of 3500 psi and temperature of 140 ˚F are displaced by neat and viscosified CO2. Breakthrough time, breakthrough recovery, and recovery at 1 pore volume injection in the horizontal orientation are the key measurements.
At the experimental conditions, CO2 breakthrough is delayed by an average of 2 times and oil recovery is increased by an average of about 20 % upon CO2 viscosification. These results reveal the effectiveness of the engineered oligomer in viscosification and improved oil recovery performance. There is no permeability loss detected in core flooding experiments.
This work sets the stage for CO2 viscosification as a viable approach as an improved oil recovery method. The process, is relatively simple and has many advantages over alternatives such as CO2-foam or water-altenative-CO2.
Effective Extraction of a Heavy Oil Resource by an Environmentally Friendly Green Solvent: Limonene.
Authors: Mathews Tanya Ann , Azzu Paul , Cortes Jairo , Hascakir Berna 
Published: September 2022

Abstract
Global oil consumption is predicted to increase by 15% from 2021 to 2050. The increasing oil demand and decreasing conventional oil supply force us to find alternate energy supplies. The key to this problem lies with the vast untapped heavy oil and bitumen resources. In this study, we investigate the effectiveness of an environmentally friendly solvent, limonene, in recovering heavy oil.
Three core flood experiments representing three different recovery methods were carried out. These include steam flooding (E1), solvent flooding (E2), and solvent-steam co-injections (E3). The green solvent, limonene, is a citrus-based non-toxic solvent. It was chosen due to its high organic solvency and ready availability. Throughout the experiments, steam was injected at a cold water equivalent of 18 ml/min, while limonene was injected at 2 ml/min. The experiments were run with a back pressure of 45-55 psi. The core pack was prepared by filling the pore space of Ottawa sand with a 60% heavy oil sample and 40% water by volume (including water percentage in oil). Produced oil and water samples were collected every 20 min during the experiments. These samples were further analyzed by emulsion characterization to determine emulsion stability and oil quality. Spent rock analyses were done to calculate the displacement efficiency of each of the experiments. In addition, an economic analysis was done to determine the optimal recovery method.
Spent rock analysis showed that a sole injection of limonene (E2) had the highest oil recovery. This confirms the high organic solvency of limonene achieved miscible flooding producing about 46 vol % from a total of 60 vol % initial oil. Steam flooding (E1), on the other hand, did not perform as well, producing around 29 vol %. The post-mortem sample from E1 indicated asphaltene precipitation which could have lowered oil recovery. Co-injection of limonene and steam was expected to yield the highest recovery due to the presence of two active drive mechanisms, thermal and miscible flooding. However, it performed comparatively less (41 vol %) than a sole injection of limonene (E2). This is further explained with emulsion characterization results. Experiments involving steam (E1 and E2) revealed strong emulsions in the oil produced, indicating a lower quality.
Furthermore, it was seen that the solvent-steam process produced weaker emulsions compared to steam flooding alone. On the other hand, solvent flooding (E2) produced high-quality oil with little to no emulsions. These results along with the economic analysis, indicate that the optimal recovery method would be solvent flooding (E2).
Our results prove that limonene is a promising organic solvent. Limonene is non-toxic, readily available, and safe to handle. As a result, it can be a safe green alternative to commonly used toxic organic solvents such as toluene.
Selection of the Flowback Rate for DFIT-Flowback Test
Authors: Wang Rui , Dahi Taleghani Arash 
Published: September 2022

Abstract
The DFIT-flowback test has shown some advantages in terms of running time and accuracy over typical injection tests such as DFITs specially in very low permeability formations. However, the success of the test depends largely on choosing an appropriate flowback rate to achieve acceptable results. The hidden assumption behind analysis is assuming uniform closure of fractures at the last step of the tests. Basically, the uniform closure is the only considered form of fracture closure in all the existing analyses for this test. Here, we show how adjusting flowback rates may change fracture closure mode and how to interpret field data accordingly. Often abnormality in the data acquired from pump-in/flowback tests have posed challenges in the widespread application of this test. Here, we use scaling analysis verified by numerical simulations to describe different situations may occur during this test and how to interpret abnormal data. Using scaling analysis does not require running complicated simulations and can provide quick solutions in field operations. Using this method can hopefully make DFIT-flowback more popular in the field.
Responsive and Controlled Release of Surfactant Encapsulated in Amino Functionalized Mesoporous Silica Nanoparticles
Authors: AlSadeg Hala , Alsmaeil Ahmed , Alhassni Mohammed , Abdel-Fattah Amr 
Published: September 2022

Abstract
Mesoporous silica nanoparticles (MSNs) have a great potential as carriers for controlled release of surfactants for enhanced oil recovery (EOR) applications. Herein, MSNs containing a cationic surfactant were surface functionalized with amino groups and their surfactant release behavior was studied and compared with that of non-functionalized MSNs. The responsive release of surfactant molecules from the mesoporous particles was studied under high salinity conditions normally encountered in subsurface environments. Fourier-Transform Infrared Spectroscopy (FTIR) analysis was carried out to characterize the functionalized particles spectroscopically. Zeta potential measurements were made to study the alteration in surface charge of the capsules. Thermal Gravimetric Analysis (TGA) was conducted to investigate the amount of encapsulated cationic surfactant in the silica capsules. Dynamic Light Scattering (DLS) and Scanning electron microscopy (SEM) analyses were performed to confirm the morphology and size of these surfactant incorporated particles in saline water containing 56,000 mg/L salts. FTIR and zeta potential data confirmed the presence of amino groups on the MSN surfaces, and the results from the TGA demonstrated that the cationic surfactant concentration is directly affected by the functionalization and amino groups bound to the MSNs. DLS and SEM analyses showed that the amino functionalized MSNs are 100 nm in size and maintain their chemical stability when present in high salinity water (HSW). IFT measurements showed that interfacial tension is reduced when the amino functionalized MSNs are suspended in HSW compared to when suspended in DI water. The oil-brine interfacial tension was reduced up to 3×10-4 mN/m when the amino functionalized MSNs are suspended in HSW. The functionalized MSNs higher IFT values when suspended in DI water indicate that the surfactant release only happens in ion rich environments which is representative of subsurface conditions. The release data indicate that the presence of the amine functional groups in MSNs results in a regulated-release mechanism where the functionalized particles in HSW released 30% of the cationic surfactant in one day. The release data indicated that the presence of the amino functional groups in MSNs improved the release properties of the encapsulated cationic surfactant. Therefore, the slow release of surfactant from these amino functionalized nanocapsules around the wellbore will result in a farther reach and deeper penetration in the reservoir.
NMR T2 Response in Rough Pore Systems: Modeling and Analysis
Authors: Li Yiteng , Alsinan Marwa , He Xupeng , Ugolkov Evgeny , Kwak Hyung , Hoteit Hussein 
Published: September 2022

Abstract
Estimating pore size distribution from NMR T2 responses typically assumes a smooth solid-pore interface. However, surface roughness accelerates NMR T2 relaxation and thus leads to an underestimation of the pore size distribution. Until now, only a few studies investigated the surface roughness effect. This work systematically studies the influence of surface roughness on NMR T2 responses and introduces a correction factor to bring incorrect T2 values back to the correct values.
This study includes three main sections: creating 3D pore structures with roughness, simulating NMR T2 relaxation using the random walk method, and quantifying the roughness effect. Constrained Latin hypercube sampling is used to create representative examples in a space-filling manner, constrained by the fast diffusion limit. Then random walk simulations are implemented, and NMR T2 responses in smooth and rough pores are calculated. To accurately estimate pore radius, a "value-to-value" model is developed to map the nonlinear relationship between a 3D roughness parameter and the proposed correction factor. The accuracy of the proposed model is validated by comparing the corrected NMR T2 responses to the reference results obtained from smooth pore systems. Numerical results show that the proposed model can correctly evaluate pore sizes from decreased NMR T2 responses caused by the surface roughness effect. Previous works incorporated this effect into surface relaxivity as they attempted to retain the pore radius and meanwhile reproduce the faster relaxation rate. However, this may break down the assumption of fast diffusion limit. Instead, this study mitigates this limitation by separating the roughness effect from surface relaxivity. The proposed correction factor offers an alternative approach to calculating the correct pore radius by accounting for the influence of surface roughness at the pore scale.
Social Media and the Oil & Gas Sector: Challenges and Opportunities
Authors: Capello Maria Angela , Cox Denise , Battalora Linda Battalora 
Published: September 2022

Abstract
There are currently 4.62 billion users of social media worldwide1. This means that more than half of the population of the world uses social media (58.4%)2. The Oil and Gas sector cannot escape this reality, which is so valuable for communications and positioning strategies. One of the top-valued goals of modern organizations in all sectors is to have a positive presence on social media. For the oil and gas sector, this is particularly needed, as energy transition concepts are not necessarily well understood nor ingrained in society at large, making it difficult to revert any negative public opinion matrix about the sector.
The COVID-19 pandemic forced many traditional organizations in the oil and gas sector to embrace social media, increasing their active presence on the main professional online platforms, gaining more engagement with their own employees and society like never before. This paper compares the social media presence of prominent organizations related to oil and gas in 2022, analyzing trends and highlighting opportunities and challenges.
A comparison of key elements considered diagnostic in improving the recognition and reputation of oil and gas organizations are addressed in more detail, in particular sustainability and DE&I (gender representation, generally addressed as Diversty, Equity and Inclusion).
Conclusions are related to cultural frameworks, selected language for postings, geo-political affinities, and the profile of the companies analyzed. Framing the current trends analyzed resulted in the identification of organizations that are more successful in the utilization of these key channels that are important to general audiences and especially to younger generations.
Some unexpected findings shaped our conclusions that strategies needed for step-changes in political or cultural settings benefit greatly from the use of social media and have proven to be effective in furthering women's empowerment and for the uptake of sustainability at the corporate level.
Scalable High-Fidelity Hydraulic Fracturing and Geo-Mechanics Simulator for Unconventionals
Authors: Valiveti Dakshina Murthy , Dyadechko Vadim , Song Ting , Gupta Varun , Sharma Akriti , Venkatesan Jagannath , Gireesh Greeshma 
Published: September 2022

Abstract
Development optimization is the key to ensuring economic extraction of hydrocarbons in unconventionals. Every dollar saved per fracture grows by 3-4 orders of magnitude per pad. Typical questions of business interest include optimal number of perforations per fracture, fluid and proppant rates, cluster spacing, well spacing, influence of pre-existing fractures and depletion on infill wells/fractures etc. Evidently, these questions span broad length scales, wide variety of governing equations, and nonlinearities. This is compounded by the challenge of tight balance between maintaining the accuracy of numerical simulations and completing simulations fast enough for sensitivity analyses.
In this work, we describe how we addressed all these challenges in building our proprietary hydraulic fracturing and geomechanics simulator. We solve the single phase porous flow equations along with Terzaghi’s effective stress based force balance equations representing the reservoir. The model includes fluid and proppant flow from well head to the specific stage through 1D compressible pipe flow. The well flow is coupled with reservoir through perforation orifice flow. Flow in fractures is considered to be the typical plane Poiseuille flow with Darcy leak-off into reservoir. We adopted scalable data structures and parallel algorithms that enable solving ~50 million degrees of freedom with relative ease. The pore-pressure is solved on a Finite Volume grid, and the deformation on Finite Element grid. All these governing equations are solved simultaneously in a fully coupled approach using an iterative solver. The fracture is assumed to be planar, defined by element interfaces and prepared a priori with deactivated duplicate nodes to avoid modifying distributed data structures during runtime. Multiple different models are implemented for well and perforation and can be chosen based on suitability. The perforations belonging to various clusters, stages and wells are activated along the timeline of completion clock, mimicking a frac-job.
The article will focus primarily on the techniques that allowed us to build such a scalable fracturing simulator, followed by simulation results. Using this simulator we are able to perform stress update calculations due to depletion, multi-well and multi-stage hydraulic fracturing scenarios. The fracture interference across stages and wells is directly captured through the governing equations. We will also present strong scaling test results to show the scalability of the simulator to millions of degrees of freedom.
Experimental Study of Proppant Transport Using 3d-Printed Rough Fracture Surfaces
Authors: Tatman G. , Bahri A. , Zhu D. , Hill A. D. , Miskimins J. L. 
Published: September 2022

Abstract
3D printing is a type of additive manufacturing technology that allows for digital 3D models to be made into physical objects out of a wide range of thermoplastics, resins, and occasionally metals. In previous years, 3D printing models at high-resolution suitable for oil and gas research was either time consuming, cost-prohibitive, or limited to a small model build volume. However, the rapid advancement in resin 3D printing technology recently has allowed for a significant increase in production speeds and model size at little cost. In this study, we utilized 3D printed rough-wall fracture panels in a large-scaled proppant transport apparatus to evaluate the feasibility of repeatable and realistic experimental investigation by the 3D printing technology.
Understanding proppant transport in hydraulically created fractures helps to answer the questions about proppant distribution, resultant fracture conductivity, effectiveness of fracture fluid and additives, and all leads to fracture treatment efficiency. In the past, lab experiments showed that fracture topography plays an important role on fracture conductivity, and the characteristics of fracture surfaces have been grouped as random distribution, channel, wavy and ledge (step-change). These surface features can be described by geostatistical parameters. For large-scale proppant transport, the realistic surfaces are difficult to create, and thus most studies have used smooth-surfaced parallel acrylic panels for the fracture walls.
Stereolithography (SLA) resin 3D printers produce a physical model by using an ultraviolet light source to selectively illuminate and cure a photopolymer onto a travelling build platform. The physical models are based on a computer-generated surface with controlled statistical definition. We have successfully printed panels to build a 4ft X 2ft main fracture with a smaller fracture intersecting orthogonally. The panels are carefully printed with transparent resin to allow for video recording. Initial tests showed the mechanical integrity of printed fractures and proppant transport results.
This paper describes the detailed procedure of generating fractures by 3D printing, experimental setup and the test results of proppant transport.
Life-Cycle Production Optimization of the CO2-Water-Alternating-Gas Injection Process Using Least-Squares Support-Vector Regression (LS-SVR) Proxy
Authors: Almasov Azad , Onur Mustafa 
Published: September 2022

Abstract
In this study, we present a framework for efficient estimation of the optimal CO2-WAG parameters for robust production-optimization problems by replacing a high-fidelity model with a least-squares support vector regression (LS-SVR) model. We provide insight and information on proper training of the LS-SVR proxy model for the CO2-WAG life-cycle production optimization problem. Given a set of training points generated from high-fidelity model-based simulation results, an LS-SVR-based proxy model is built to approximate a reservoir-simulation model. The estimated optimal design parameters are then found by maximizing NPV using the LS-SVR proxy as the forward model within an iterative-sampling-refinement optimization algorithm that is designed specifically to promote the accuracy of the proxy model for robust production optimization. As an optimization tool, the sequential quadratic programming (SQP) method is used. CO2-WAG design variables are CO2 injection and water injection rates for each injection well at each cycle, production BHP for each production well at each WAG half-cycle, and inflow control valve (ICV) for each well at each WAG half-cycle and at each valve. We study different scenarios where we fix some of the design variables to investigate the importance of design variables on life-cycle production optimization of the CO2-WAG problem. We compare the performance of the proposed method using the LS-SVR runs with the popular stochastic simplex approximate gradient (StoSAG) and reservoir-simulations runs for a synthetic example considering a three-layer, channelized reservoir with 4 injectors and 9 producers. Results show that the proposed LS-SVR-based optimization framework is at least 3 to 6 times computationally more efficient, depending on the cases considered, than the StoSAG using a high-fidelity numerical simulator. However, we observe that the size and sampling of the training data, as well as the selection of well controls and their bound constraints for the well controls, seem to be influential on the performance of the LS-SVR-based optimization method. This is the first LS-SVR application to the CO2-WAG optimal well-control problem. The proposed LS-SVR-based optimization framework has great potential to be used as an efficient tool for the CO2-WAG optimization problem.