bluuebunny/crossref_metadata_2025 huggingface dataset:
The Spectrum of Cardiovascular Complications in COVID-19- A Comprehensive Literature Review
Authors: Mushtaque Raja Shakeel , Mushtaque Rabia , Baloch Shahbano , Raza Aadil , Bhatti Haseeb , Khan Zohaib
Published: August 2020

A newly identified novel coronavirus named as severe acute respiratory syndrome-related coronavirus2 (SARS‐CoV 2) has given rise to the global pandemic. SARS-CoV2 which causes coronavirus disease 2019 (COVID-19), is a positive-stranded RNA virus with nucleocapsid. It binds to host angiotensin-converting enzyme2 (ACE2) receptor through surface glycoprotein (S protein). These ACE 2 receptors are attached to the cell membranes of many organs. Thus, COVID-19 does not only result in acute respiratory distress syndrome but also affects multiple organ systems, requiring a multidisciplinary approach to manage this disease. COVID-19 can damage the myocardial cells and result in fulminant myocarditis, acute cardiac injury, cardiomyopathy, heart failure, cardiogenic shock, or arrhythmia. COVID-19 seeds harmful immune response through cytokine storm leading to indirect organ damage. In this literature review, the available data is comprehended regarding cardiovascular complications in COVID-19, and the correlation of biomarkers with the disease activity is discussed. This literature review also highlights the important treatment options and outcomes of the individual study.
A Novel Small Molecule, 1,3-di-m-tolyl-urea, Inhibits and Disrupts Multispecies Oral Biofilms
Authors: Kalimuthu Shanthini , Cheung Becky P.K , Yau Joyce Y.Y , Shanmugam Karthi , Solomon Adline Princy , Neelakantan Prasanna
Published: August 2020

Imbalance of homeostasis between the microbial communities and the host system leads to dysbiosis in oral micro flora. DMTU (1,3-di-m-tolyl-urea), is a biocompatible compound that was shown to inhibit Streptococcus mutansbiofilms by inhibiting its communication system (quorum sensing). Here, we hypothesized that DMTU is able to inhibit multispecies biofilms. We developed a multispecies oral biofilm model comprising an early colonizer Streptococcus gordonii, a bridge colonizer Fusobacterium nucleatum, and late colonizers Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans. We performed comprehensive investigations to demonstrate the effect of DMTU on planktonic cells and biofilms. Our findings showed that DMTU inhibits and disrupts multispecies biofilms without bactericidal effects. Mechanistic studies revealed significant down regulation of biofilm and virulence related genes in P. gingivalis. Taken together, our study highlights the potential of DMTU to inhibit polymicrobial biofilm communities and their virulence.
Framed Experiments and Games in Agriculture: A Systematic Review of the 21st Century in Economics and Social Science
Authors: Hernandez-Aguilera J. Nicolas , Mauerman Max , Herrera Alexandra , Vasilaky Kathryn , Baethgen Walter , Loboguerrero Ana M. , Diro Rahel , Tesfammariam Yohana , Osgood Daniel
Published: August 2020

Framed experiments and games are a useful medium to understand how context affects individual and group decision-making. They are particularly relevant for field research in agriculture, where alternative experimental designs can be costly and unfeasible. After a systematic review of the literature, we found that the volume of published studies employing coordination and cooperation games increased during the 2000-2020 period. In recent years, there has been greater attention given to natural resource management, conservation, and ecology areas, especially in strategic regions for agriculture sustainability. Other games, such as trust and risk games, have come to be regarded as standards of framed field experiments in agriculture. Regardless of sectoral focus, most games' results are subject to internal and external validity criticism. In particular, a significant portion of the games showed potential recruitment biases against women and no opportunities for a continued impact assessment. However, games' validity should be judged on a case-by-case basis. Specific cultural aspects of games might reflect the real context, and generalizing games' conclusions to different settings is often constrained by cost and utility. Overall, games in agriculture could benefit from more significant, frequent, and inclusive experiments and data – all possibilities offered by digital technology. Present-day physical distance restrictions may accelerate this shift. New technologies and engaging ways to approach farmers might represent a turning point for games in agriculture in the 21st century.
Enhancing Password Authentication Using Association Password Technique: An Ecological Theory of Memory and Data
Authors: Commodore Raymond , Hayfron-Acquah J. B.
Published: August 2020

The Study proposes possible solution to enhance Password Authentication using Association Technique based on the Ecological theory of memory and data at the Presbyterian university College Ghana. The study used a deductive research approach and employed two empirical Studies using the non-probability sampling technique where few respondents were selected in categories out of the populace by means of openness in other to get similar categories of respondents with different age groups and education background. The two Empirical study also used a quasi-experimental approach which structure incorporate observation, experimental treatment and timing. The First empirical study carried out an investigation to identify existing Password authentication Technique used by End Users, as well as their behavior in password utilization through a self-completed questionnaires which was analyzed using SPSS version 21 . The Second empirical study was an experiment to compared three kinds of password constructions that is own set, modified dictionary, and association against one another to see which of them would be best meet the ecological theory of memory and data which aims at creating a secured password that is easy to recall. The computation and evaluation of password construction was done using My1login Password meter whiles Levenshtein Distance String Edit Software was also used to compute the memorability of all given password. Across-tabulation was then employed out of the experiment using SPSS version 21. The result from the analysis revealed that the majority of the respondents do have weak passwords and also have few passwords which they even end up sharing with families and friends and reuse it. This confirms statements made by researchers that human being is the weakest connection in information system securities. To maintain Confidentiality, Availability and Integrity of data, the study therefore recommended the use of the Association Password technique which makes it easier to develop a much secured password that is difficult to crack but easy remember.
PhotonLabeler: An Inter-disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data
Authors: Malambo Lonesome , Popescu Sorin C.
Published: August 2020

NASA’s ICESat-2space-borne photon-counting lidar mission is providing global elevation measurements that will provide significant benefits to a variety of bio-geoscience research applications. Given the novelty of elevation and the derived data products from the ICESat-2 mission, the research community needs software tools that can facilitate photon-level analyses to support product validation and development new analysis methods. Here, we describe PhotonLabeler, a free graphic user interface (GUI) for manual labeling and visualization of ICESat-2 Geolocated Photon data (ATL03). Developed in MATLAB, the GUI facilitates the reading and display of ATL03 Hierarchical Data Format (HDF) files, the manual labeling of individual photons into target classes of choice using a number of point selections tools and enables eventual saving of labeled data in ASCII format. Other capabilities include saving and loading of labeling sessions to manage labeling tasks over time. We expect labeled data generated using the application to serve two main purposes. First, serve as ground truth for validating various products from ICESat-2 mission, especially for study sites around the world that do not have existing reference datasets such as airborne lidar. Second, serve as training and validation data in the development of new algorithms for generating various ICESat-2 data products. We demonstrate the first use case through a validation case study for the land and vegetation product (ATL08), which provides canopy and terrain height estimates, over two sites. For the first site, located in northwestern Zambia, we used ICESat-2 ATL03 data acquired at night and for our second site in Texas, US, we used ATL03 data acquired during the day. The PhotonLabeler application is freely available as a compiled MATLAB binary to enable free access and utilization by interested researchers.
Measurement of Oil-Gas Diffusivity at Reservoir Conditions for Huff-n-Puff EOR in Shales
Authors: Mukherjee Sanchay , Dang Son T. , Rai Chandra S. , Sondergeld Carl H.
Published: August 2020

Due to the extremely low permeability and high depletion rate, primary recovery from unconventional reservoirs is generally low. Huff-n-puff has proved to be a successful EOR technique in tight formations, such as the Eagle Ford. However, the underlying transport mechanism remains to be completely understood. Recent studies show oil-gas diffusion is a key factor for the success of huff-n-puff EOR. Due to concentration gradient, injected gas molecules diffuse into in-situ oil causing it to swell and consequently to be expelled out of the nanopores into the micro- and macro- fractures.

Our research group has designed an experiment with a high pressure-high temperature cell having observation windows for the measurement of oil swelling and diffusivity in oil-gas mixtures and in this study, we present some preliminary results. The measurements were done on a Meramec oil (API-42.7) with 3 different gas mixtures of methane – ethane, at a temperature of 175°F to evaluate the impact of injection pressure (above and below Minimum Miscibility Pressure-MMP) and injectate composition on oil-gas diffusivity. The diffusivity of injectate gas into oil phase as a function of pressure increases to maximum at MMP, beyond which it decreases. Using pure methane (MMP = 5500 psi) as the injectate, the diffusion coefficient increases by 250% on increasing the pressure from 2500 psi to 5500 psi and then decreases. Based on the data available in the literature, this decrease in diffusivity can be explained by the increase in bulk fluid density and viscosity. For the oil sample used in this study, the diffusion coefficient varies between 10−10 m2/s to 10−9 m2/s, regardless of pressure and injectate composition.

Tight reservoirs generally have high matrix tortuosity, which impacts the diffusion efficiency in the porous media. Using tortuosity values available in the literature and diffusivities of oil gas systems measured in this study, we estimate that the injected gas can only travel 0.2-0.75 ft away from the fracture-faces in 1-6 months of injection. This study highlights the importance of stimulated reservoir area (SRA) characterization, nanoporous tortuosity and diffusivity measurements to optimize huff-n-puff recovery in shales.
Scleroglucan Polymer Injectivity Test Results in the Adena Oilfield
Authors: Muhammed Farag , Dean Elio , Pitts Malcolm , Wyatt Kon , Kozlowicz Briana , Khambete Malhar , Jensen Tryg , Sumner Eric , Ray Charles
Published: August 2020

Reservoirs with harsh environments are now being routinely evaluated for applications of chemical EOR. High temperatures and high salinity water are proving to be hurdles chemical manufacturers must overcome. Scleroglucan is a biopolymer with robust viscosifying power, excellent stability under high temperature, high salinity, and resistance to shear. An injectivity test was conducted in the high temperature (180 °F) Adena oilfield to evaluate the injectivity of scleroglucan polymer.

Field injectivity test results are compared to those from the laboratory. Polymer parameters evaluated include polymer viscosity, polymer shear, resistance factor, and residual resistance factor.

The unique feature of this injectivity test is the bottom-hole pressure data that allowed for direct field measurement of resistance factor and the evaluation of multiple fall off tests. Pressure transient analysis (PTA) allowed for (1) skin to be measured before and after polymer injection to evaluate sand face plugging, and (2) permeability measurements that were used for direct field measurement of residual resistance factor.

Conclusions from the injectivity test in the Adena field are: Scleroglucan was successfully injected into a harsh reservoir environment. PTA data provided a field based direct measurement of resistance factor (RF) and residual resistance factor (RRF).PTA fall off test indicated no sand face plugging, in that a constant skin was observed at the well before and after the polymer injectivity test.RRF was measured at the sand face via FBHP and several feet into the reservoir via PTA. Sandface RRF was 1.3, indicating a 25% reduction in permeability, while PTA based permeability (larger radius of investigation) was reduced by 50%, the equivalent of a RRF of 2.Skin for the two fall off tests, before and after polymer injection, show the polymer did not plug nor exacerbate the pre-existing formation damage.

The first field injection of EOR–grade scleroglucan was successful. The use of BHP data and fall off testing allowed for field-based values of resistance factor and residual resistance factor to be measured.

Typically, these parameters are laboratory derived values and uncertainty exists when scaling up the process. The use of pressure transient analysis in polymer injectivity tests offers an economical option for field evaluation of polymer based EOR technologies.
Measurement of Transport Properties and Densities of Dimethyl Ether DME and Water/Brine Mixtures
Authors: Cui Jingyu , Qi Yunying , Dindoruk Birol
Published: August 2020

Dimethyl ether (DME) is considered to be a potential Enhanced Oil Recovery EOR agent for enhanced waterflooding. Due to its first contact miscibility in hydrocarbons and partial high solubility in water/brine, it partitions preferentially into the hydrocarbon phase upon contact when DME-brine solution is injected into the reservoir. As a result, the residual oil swells and its viscosity is reduced which in turn leads to significantly higher ultimate oil recovery. The amount of swelling and viscosity-reduction depends on the extent of DME partitioning and its availability along with the systems pressure and temperature. In the DME-oil mixing zone, and DME-water zone, the estimation of the DME-Hydrocarbon and DME-water viscosities is crucial to evaluate and understand the performance of DME-enhanced waterflooding (DEW) at reservoir or lab/pilot-scale. Among those, there is no systematic viscosity data found for DME-brine systems, especially for the condition of interest (reservoir conditions). Viscosity of DME-Hydrocarbon follows the traditional mixing rules and expectations quite well; while viscosity of DME-water shown to exhibits very different behavior than expected. In this paper, we present new data on the systematic density and viscosity measurements for DME and Water for the first time. Such essential transport data is necessary to be able to evaluate the DME/DEW injection potential for various applications, from EOR/IOR to near wellbore stimulation.

Some of the important features of this study are:

New data for the literature to be used for DME and DME enhanced waterflooding Correlation development for the measured data.
Joint Optimization of Well Completions and Controls for CO2 Enhanced Oil Recovery and Storage
Authors: Chen Bailian , Pawar Rajesh
Published: August 2020

CO2 storage through CO2 enhanced oil recovery (EOR) is considered as one of the technologies to help promote larger scale deployment of CO2 storage because of associated economic benefits through oil recovery, 45Q tax credits and the utilization of existing infrastructure. The objective of this study is to demonstrate how optimal reservoir management and operation strategies (including well completions and controls) can be used to optimize both CO2 storage and oil recovery.

The optimization problem was focused on jointly estimating the well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO2 injection/oil production controls that maximize the net present value (NPV) in a CO2 EOR and storage operation. We utilized the newly developed StoSAG algorithm, one of the most efficient optimization algorithms in the reservoir management community, to solve the optimization problem. The performance of joint optimization approach was compared with the performance of well control only optimization approach. In addition, the performance of co-optimization of CO2 storage and oil recovery approach was compared with the performances of maximization of only CO2 storage and maximization of only oil recovery approaches.

The optimization results showed that a joint optimization of well completions and well controls can achieve an 8.84% higher final NPV than the one obtained from the optimization of only well controls. It was observed that the NPV incremental for joint optimization is mainly due to the fact that the optimal well completions and controls approach results in efficient CO2 storage and oil production from different reservoir layers depending on the differences in individual layer properties. Comparison of co-optimization (i.e., maximization of NPV) and maximization of only CO2 storage or only oil recovery showed that the co-optimization and maximization of only oil recovery result in significantly higher final NPV than that obtained through maximization of only CO2 storage approach while maximization of only CO2 storage can achieve significantly higher CO2 storage in the reservoir compared to the other two scenarios. The similar results for co-optimization and maximization of oil production are obtained because of the difference in oil revenue compared to CO2 storage tax credit.

To the best of our knowledge, this is the first study in oil/gas industry and CO2 storage community to perform joint optimization of well completions and well controls in the fields. We expect that the proposed optimization framework will be a useful and efficient tool for field engineers to optimally manage CO2 EOR projects to maximize revenue through oil recovery as well as CO2 storage by taking advantage of the new 45Q tax law.
Prediction of CO2 Minimum Miscibility Pressure MMP Using Machine Learning Techniques
Authors: Sinha Utkarsh , Dindoruk Birol , Soliman Mohamed
Published: August 2020

Minimum Miscibility Pressure (MMP) is a key design parameter for gas injection projects. It is a physical parameter that is a measure of local displacement efficiency while subject to some constraints due to its definition. Also, MMP value is used to tune compositional models along with proper fluid description. In general, CO2 and Hydrocarbon gases are the most common gases used for (or screened for) gas injection processes and due to recent focus to screen for the coupling of CO2-sequestration and CO2-EOR projects. As CO2-Oil phase behavior is quite different than the hydrocarbon gas-oil phase behavior, researchers developed specialized correlations for CO2. Therefore, there is a need for a tool with expanded range capabilities for MMP for CO2 gas streams. The only known measurement technique for MMP that is coherent with its definition is the use of a Slim-Tube which also restricts the amount of data available even though there are other alternative techniques presented over the last 3 decades which all suffer from various limitations. Since correlations are inexpensive one of the inexpensive and easy ways to calculate the MMP, therefore there have been several correlations developed in past based on correlative physics [9], [18], [24], [28], [50], [80], [82] and phase behavior properties of the oil - CO2 mixture [3], [5], [44]. This paper present two separate approaches to calculating the MMP of oil during pure CO2 injection, (1) Analytical correlation where the correlation coefficients were tuned using linear SVM [39], [67] and 2) using a hybrid method (combination of random forest regression [11] and proposed correlation) which very nicely captures the dynamic behavior of CO2. The model takes the compositional analysis of oils up to heptane plus fraction, molecular weight of oil, and reservoir temperature as input parameters. Based on statistical analysis and cross-plots we showed that the performance of the final proposed method is superior to all the leading correlations [9], [18], [24], [28], [50], [80], [82] and supervised machine learning [55] methods considered in this work [10], [11], [14], [15], [39], [67]. The proposed model works for the widest spectrum of MMP from 1000 to 4900 psia which cover the entire range oils within the scope of CO2 EOR based on the screening criteria [54], [75].
Successful Field Implementation of CO2-Foam Injection for Conformance Enhancement in the EVGSAU Field in the Permian Basin
Authors: Katiyar Amit , Hassanzadeh Armin , Patil Pramod , Hand Michael , Perozo Alejandro , Pecore Doug , Kalaei Hosein , Nguyen Quoc
Published: August 2020

This paper presents the performance of a CO2 foam injection pilot implemented in the East Vacuum Grayburg San Andres Unit (EVGSAU) by ConocoPhillips in cooperation with The Dow Chemical Company. The pilot project focuses on a single CO2 injection pattern, consisting of one injector and eight producers, selected due to signs of early gas breakthrough and poor overall sweep efficiency.

To solve these conformance issues and increase overall pattern production performance, a new foaming surfactant with low adsorption and high gas partitioning characteristics was developed and experimentally tested at simulated reservoir conditions. A "water alternating surfactant-in-gas" injection strategy was created utilizing a history matched reservoir simulation model and an empirical foam model. This reservoir model was also utilized to better understand the dependency of surfactant concentration on foam generation and fluid diversion. Injection profile logs (IPLs) were also run, in both water and CO2 phases, prior to pilot implementation to establish baseline injection performance.

This paper will detail several performance indicators that illustrate sustained improvement in pattern injection and production after more than 15 cycles of alternating water, CO2+surfactant, and CO2-only injection. During each cycle, gas injectivity trends were calculated and compared to the baseline to monitor foam strength and performance. Four additional IPLs were run, which indicated continuous improvement in vertical sweep efficiency and ultimately resulted in uniform injection distribution between the upper and lower sections of the producing zone. Finally, the most significant result of the trial was the uplift in pattern oil production. It has averaged ~20% above the baseline production forecast throughout the entire pilot period and peaked within the first six months at ~60% above the baseline.

The success of this pilot illustrates the benefits of using a low adsorbing and CO2 soluble foaming surfactant to address reservoir conformance issues for CO2 floods. Further optimization of the pilot based on the simulation forecast is planned to improve long-term pilot economics.
Artificial Diagenesis of Carbonates: Temperature Dependent Inorganic and Organic Modifications in Reservoir Mimetic Fluids
Authors: Rao Ashit , Kumar Saravana , Annink Carla , Le-Anh Duy , B. Alotaibi Mohammed , C. Ayirala Subhash , Siretanu Igor , Duits Michel , Mugele Frieder , A. Yousef Ali
Published: August 2020

Within reservoirs, spatial variations related to mineralogy and fluid chemistry determine the success of improved oil recovery (IOR) techniques. However, the composition and structure of mineral-adsorbent-fluid interfaces, which fundamentally determine the initial and IOR-altered wettability of reservoir rocks as well as the displacement of crude oil (CRO), are unclear. Replicating the diagenetic alterations of carbonates, this study addresses the temperature dependence of the inorganic and organic modifications of calcite by reservoir pertinent fluids as well as its consequences on mineral wettability and reactivity.

We utilize a suite of characterization methods, such as confocal Raman, scanning electron and atomic force microscopy as well as Fourier-transform infrared spectroscopy, to investigate the modifications of carbonates on aging in formation water (FW), CRO-equilibrated FW and FW-equilibrated CRO. The microscopic modifications of carbonates present positive correlations with aging temperature and also are varied, encompassing topographical alterations, cation substitution of lattice Ca2+ ions by Mg2+ ions and the deposition of particles enriched with polyaromatic hydrocarbons (PAHs) as organic adlayers. Aging in the formation waters produce substantial reconstruction of calcite surfaces, with the formation of Mg-calcite layers at elevated temperatures. Subsequent aging in brine-equilibrated CRO produces an organic coating on calcite surfaces, which is composed of PAH-enriched particles. The organic adlayers, deposited at high temperature, produce a transition in the macroscopic contact angles towards a more ‘oil wet’ tendency. In addition, the organic adlayer presents limited permeability and serves as a diffusion barrier to the reactivity of the bound mineral, as evident from substantially reduced rates of calcite dissolution. The multilayer deposition of organic particles is attributed to an interplay between bulk and surface reactions for interfacially active constituents of CRO. With the enrichment of PAHs even observed for mineral grains within reservoir rocks, the permeability and stability of organic adlayers emerge as key factors determining the wettability of carbonates as well as the diffusion behavior of ionic and molecular species at mineral-fluid interfaces.

Results of this study are relevant to multiple aspects of reservoir development and maintenance, encompassing laboratory scale wettability and core flooding experiments, in silico models as well as the advancement of IOR strategies. The observed nano- and microscopic surface alterations of carbonates within reservoir mimetic environments facilitate our understanding of the physicochemical relations between mineralogy and fluid chemistry as well as elucidate the organization of mineral-adsorbent-fluid interfaces within reservoirs.
Integration of Capacitance Resistance Model with Reservoir Simulation
Authors: Davudov Davud , Malkov Anton , Venkatraman Ashwin
Published: August 2020

Capacitance resistance models (CRM) provide an analytical framework to characterize and optimize water flooding fields. There are significant challenges in adapting these methods to actual field data with many complexities. In this research, we present a novel approach to integrate CRM models with reservoir simulation to improve reservoir characterization as well as identify new injection strategies to increase oil recovery. The results of this integration are presented for a specific field with challenging geological uncertainties.

In particular, the historical production and injection data taken from water flooding field has been analyzed and separated as training and prediction part. First, inter-well connectivity (gain) values are estimated based on training part of the data which are further verified with streamline simulation results. A comparison of allocation factors between wells from the reservoir simulation model and the inter-well connectivity is presented to showcase consistency. Next, the prediction capability of the model has been verified with the testing section of data. Finally, for the next future 3 years, oil production rates obtained from CRM is further verified with results from reservoir simulation.

The large number of wells and the uncertainties associated with a producing field makes CRM modeling a challenge especially for predictions. Accordingly, initial screening and analysis of field data is an essential part for successful CRM application. After examining field data with 5 injectors and 21 producers which is subject of this study, it has been observed that only 6 wells are positively correlated with injectors which has been used as an input for CRM. Results further indicate that, with correct application of CRM, for the selected wells future oil recovery can be predicted with less than 2% differences compared to simulation results. This shows the capability and practicality of CRM. The model is next used to obtain new injection schedule to increase oil recovery. The new injection rates obtained from the model predict an increase in oil recovery by 5-10%.

The continuous recording of production and injection data presents a new opportunity to integrate analytical approaches with traditional reservoir simulation approach for effective reservoir management. The presented model that includes verification of CRM results (with streamlines as well as reservoir simulation) helps benchmark these techniques that are simple and effective. The presented approach is particularly applicable for mature fields where historical production and injection data is available so that data-driven models (CRM) can be integrated with traditional reservoir simulation models.
Compositional Simulation of Cyclic Gas Injection in Liquid-Rich Shale Reservoirs Using Existing Simulators with a Framework for Incorporating Nanopores
Authors: Bi Ran , Luo Sheng , Lutkenhaus Jodie , Nasrabadi Hadi
Published: August 2020

The current models for predicting the phase behavior of gas injection in shale can be highly unreliable because nanopores (with diameters less than 50 nm) form a significant pore volume in many shale formations. Conventional PVT models cannot describe the phase behavior in nanopores. Here, we present a practical framework to regenerate the PVT considering the shale nanopores effect for a more reliable compositional simulation of gas injection in shale reservoirs by using existing commercial simulators.

The pore-size distribution in shale reservoirs can be discretized into a bulk-region (fractures and macropores) and nanopores. We use a pore-size-dependent equation of state (PR-C EOS) to describe the phase behavior of the fluid for each pore. Bulk fluid characterization with laboratory PVT reports determines the bulk fluid parameters for the PR-C EOS. The confinement parameters for the PR-C EOS are from the reported database (Luo et al. 2018a). Further, multi-scale phase equilibria are calculated by minimizing the free energy. We model the multi-scale constant composition expansion and constant volume depletion with volume expansion per stage. The modeling generates multi-scale PVT (formation volume factor, saturation, etc.) for the shale reservoir, which is used to retrain the Peng–Robinson equation of state (PR EOS) by modifying the acentric factor, binary interactions, and critical temperature and pressure. The retrained PR EOS is then applied in a commercial compositional simulator to forecast gas injection improved oil recovery (IOR) in shale. We also use the updated gas saturations in the multi-scale PVT model to modify the relative permeability tables used in the compositional simulation.

We predict significantly higher gas production and lower oil production when the effect of shale nanopores on the phase behavior and updated relative permeability are considered in the compositional simulation of the primary depletion of shale reservoirs. In the gas injection improved oil recovery (IOR) stage, the cumulative oil production is enhanced with both the original and multi-scale PVT models. However, when the effect of nanopores is not considered in the compositional simulation, the increases in the cumulative oil production and cumulative gas production can be underestimated and overestimated, respectively. This can have significant consequences on the economic evaluation of the gas IOR projects in shale reservoirs.

The application of multi-scale phase equilibria in shale reservoirs is challenging in compositional simulators. Our proposed framework enables engineers to incorporate multi-scale phase equilibria from the PR-C EOS in their shale reservoir simulations. It does not require a change in the cubic equations of state in current developed commercial compositional simulators, thus preserving the efficiency of the compositional simulators.
A Novel EOR Technique for the Attic Oil in Dipping Faulted Reservoirs by Utilizing Gas Oil Countercurrent and Water Flooding Assistance
Authors: Ma Kang , Jiang Hanqiao , Dong Rencheng , Wheeler Mary , Li Junjian , Zhang Rongda
Published: August 2020

After long-term water flooding in dipping faulted reservoirs, attic oil is formed and located above the structurally highest wells. A novel technique that combines the Gas Oil Countercurrent (GOC) and Water Flooding Assistance (WFA) is proposed in this paper in order to recover this type of remaining oil. The basic GOC mode includes three procedures, that is, gas injection, well shut-in to form a Secondary Gas Cap (SGC), and production. For the new method GOC-WFA, the WFA is considered in the gas injection and production stage. In this paper, the basic GOC and GOC-WFA experiments are performed to elaborate the EOR mechanism and efficiency of the new method. Three experiment cycles are performed in each experiment. The experiment results illustrate that the WFA can improve the production efficiency by shortening the well shut-in time. The SGC condition is much better in GOC-WFA compared to the GOC in the same well shut-in time. The well shut-in time can be shortened by 50%. In the production stage, the SGC expansion and WFA create Double Displacement Process (DDP). The WFA can inhibit the gas channeling and lower the pressure decline rate. Besides, WFA can also displace the remaining oil located between the production and injection well that cannot be displaced by the gas cap expansion. Compared to the basic GOC, the total oil production volume is nearly doubled. Based on the production model of GOC-WFA, the sensitivity of various operational and geological parameters is analyzed by the reservoir simulation method. Then, the fault-block reservoir screening condition for GOC-WFA is established; the injection-production parameters in the gas injection and production stage are optimized. Finally, the EOR feasibility of the GOC-WFA in the fault-block reservoir is testified by the experimental and simulation results. Therefore, the GOC-WFA can effectively enhance oil recovery in the sealed mature fault-block reservoir.
Improvements on Modelling Wettability Alteration by Engineered Water Injection: Geochemical Pore-Scale Approach
Authors: Bordeaux Rego Fabio , Mehrabi Mehran , Sanaei Alireza , Sepehrnoori Kamy
Published: August 2020

Several laboratory experiments demonstrated that different water compositions cause rocks to change from oil- to water-wet state. Although it is a consensus that wettability alteration is the main recovery mechanism, modeling the underlying mechanism is still a major challenge. Our main goal is to improve and validate a physically based model to predict contact angles from zeta-potential measurements. We propose a new mass-action formulation for surface complexation model (SCM) that includes the energy interaction effect between two close surfaces (PS). Currently, most SCMs consider rock and oil as isolated surfaces (IS). Thus, we hypothesize that, as rock and oil surface approach each other, PS model produce a better description of electrostatic distribution. Additionally, we develop a method of determining SCM equilibrium constants to fit several zeta-potential measurements for different ion concentrations (Na+, Ca2+, Mg2+, SO42- and H+). Finally, we estimate contact angles using disjoining pressure calculations and compare them with ones reported in the literature. From a SCM set of reactions available in the literature, we validate the developed IS model against PHREEQC (a reference simulator for geochemical reactions). For the PS case, the system of equations’ solution is very close to IS approach when the interaction between surfaces are negligible (wide spacing between surfaces). Regarding zeta-potential prediction for calcite-brine system, we argue that Na+ might not be an indifferent ion as suggested previously. Our simulation results indicate that, besides the renowned potential-determining ions, sodium adsorption on calcite can play an important role in electrostatic interactions, switching surface charge polarity. Thus, we only achieve a successful fit of zeta-potential measurements when Na+ is considered in the SCM reactions. Finally, contact angle estimation using the PS model and disjoining pressure theory provide good predictions of seven different cases reported in the literature. We validate our method on a total of 66 and 163 contact angle and zeta-potential measurements, respectively. The present work is a novel approach to represent how electrostatic interactions among rock, brine and oil modify the rock surface charge and the rock wetting state.
Simulation and Thermodynamic Modeling of Solvent EOR and Bitumen Recovery in Organic-Rich Tight Reservoirs
Authors: Neshat Sajjad , Okuno Ryosuke , Pope Gary
Published: August 2020

This paper introduces a new approach for using solvents for enhanced oil recovery from organic-rich unconventional reservoirs. The heavy organic components in the reservoir rock, i.e. bitumen, are included in the phase behavior model using a cubic equation-of-state. The phase behavior of mixtures of methane, CO2, and dimethyl ether (DME) with reservoir hydrocarbons including bitumen was studied to better understand the interaction of each solvent with reservoir fluids including water in the case of DME. The phase behavior models were then used in an equation-of-state compositional reservoir simulator to explore the potential of each solvent to increase the oil recovery including otherwise immobile bitumen from a 3D heterogeneous reservoir.
A Data-Driven Approach to Forecasting Production with Applications to Multiple Shale Plays
Authors: Xiong Hao , Kim Changjae , Fu Jing
Published: August 2020

Decline curve analysis has been used as a reliable method to forecast conventional reservoir well production over the last decades. Recently, an increase in the demand for oil and gas has caused unconventional reservoirs to become a prominent source of energy. However, it is challenged if we still apply the decline curve analysis in unconventional reservoirs due to its limitations such as boundary dominated flow, constant operation condition, et al. Therefore, in this paper, two new methods are proposed using machine learning method to forecast well production in unconventional reservoirs, especially on the EOR pilot projects.

The first method is the Neural Network, which allows the analysis of large quantities of data to discover meaningful patterns and relationships. Both peak production rate and hydraulic fracture parameters are used to be the key factors. Lastly, Neural Network technology is applied to investigate the relationship between key factors and oil production rate. The second method uses the Time Series Analysis. Time Series Analysis is one of the most applied data science techniques in business and finance. Since the properties of unconventional reservoir make the production prediction more difficult, it is safe to say that Time Series Analysis can yield good results on the production rate forecast.

Field production data from over 1000 wells from different shale plays (Barnett, Bakken, Bone Springs, Eagle Ford oil, Eagle Ford gas, Fayetteville, Marcellus gas, Marcellus oil, Utica oil, and Woodford) is used to verify the feasibility of these two methods. The results indicate there is a good match between the available and predicated production data. The overall R values of Neural Network and Time Series Analysis are above 0.8, which demonstrates that Neural Network and Time Series Analysis are reliable to study the dataset and provide proper production prediction. Meanwhile, when dealing with the EOR production prediction, such as Huff-n-Puff, Time Series Analysis shows more accurate results than Neural Network.

This paper proposes a thorough analysis of the feasibility of machine learning in multiple unconventional reservoirs. Instead of repeatedly fitting the production data by decline curve analysis, it also provides a more robust way and meaning reference for the evaluation of the wells.
Application of Tracer Based Workflow for Calibrating Reservoir Heterogeneity
Authors: Doorwar Shashvat , Purswani Prakash , Ambastha Anil , Jain Lokendra , Thach Sophany
Published: August 2020

Capturing the correct reservoir heterogeneity in a geological model is critical for designing and accurately forecasting expected production benefits from improved/enhanced oil recovery (IOR/EOR) processes. In simple terms, reservoir heterogeneity is often considered as a measure of statistical variation of static properties, such as porosity and permeability. Lorenz coefficient and Dykstra-Parsons coefficient are two such measures of reservoir heterogeneity that account for these static effects. These measures are considered simplistic because the spatial distribution and arrangement of these properties is more critical for reservoir characterization than its statistical variation. Dynamic Lorenz coefficient is one such measure that accounts for the spatial distribution and arrangement of porosity and permeability. Dynamic Lorenz coefficient cannot be directly measured in the field but can be implicitly inferred from tracer data. This inferred heterogeneity will be influenced by the spatial distribution of static properties and can also be significantly influenced by multiphase flow effects, such as, viscous fingering and gravity over/under-ride which often arise from the differences in the viscosities and densities of the different phases involved. Dynamic Lorenz coefficient interpreted from a tracer test response lumps both static and multiphase (dynamic) effects into one measure of heterogeneity. During geological model construction, dynamic Lorenz coefficient is also used to rank the model in terms of heterogeneity to select the most representative model. However, the geological models are ranked using fast single-phase/streamline simulations and are devoid of complications caused by adverse mobility or density effects. This creates a disconnect between the heterogeneity measures used to characterize a geological model and those available to characterize a reservoir. Thus, calibrating a geological model to field data is a laborious task.

In this paper, we present a workflow that bridges this gap by decoupling the effect of adverse mobility to obtain an approximate measure of heterogeneity that can be cross-checked against the geological realizations to select the most representative model. The workflow developed in this paper is for inverted, seven-spot patterns and is mainly focused on water-wet reservoirs.
EOR Screening Including Technical, Operational, Environmental and Economic Factors Reveals Practical EOR Potential Offshore on the Norwegian Continental Shelf
Authors: Smalley P. Craig , Muggeridge Ann H. , Amundrud Sølvi S. , Dalland Mariann , Helvig Ole S. , Høgnesen Eli J. , Valvatne Per , Østhus Arvid
Published: August 2020

We present a novel advanced EOR screening approach, adding to an existing technical screening toolkit powerful new practical discriminators based on: (1) Operational complexity of converting existing offshore fields to new EOR processes; (2) Environmental acceptability of each EOR process, given current field configuration; (3) Commercial attractiveness and competitiveness. We apply the new approach to 14 EOR processes across 85 reservoirs from 46 oilfields and discoveries on the offshore Norwegian Continental Shelf (NCS).

When the operational, environmental and economic thresholds were included, 45% of the technical opportunities were screened out, and the overall potential recovery increment was ~280 MSm3 (million standard cubic metres), the top processes being HC miscible, low salinity/polymer, low salinity, CO2 miscible, gels. Excluding environmental factors (i.e., assuming environmental issues could be solved by new technologies), the increment is ~340 MSm3, indicating a ~60 MSm3 prize for research into environmentally benign EOR methods. The economic thresholds used here were intentionally set low enough to eliminate only severely commercially challenged opportunities; using higher commercially competitive thresholds would reduce the overall volumes by a further ~40 MSm3.

The extension of EOR screening to include operational, environmental and economic criteria is not intended as a substitute for in-depth studies of these factors, but it should help stakeholders make earlier and better-informed decisions about selection of individual EOR opportunities for deeper study, leading to piloting and eventual field-scale deployment. Revealing the sensitivity of each EOR process to operational, environmental and economic factors will also help focus R&D onto the practical, as well as technical, barriers to EOR implementation.
Successful Foams EOR Field Pilot in a Naturally Fractured Reservoir by the Injection of the Foaming Agent Dispersed in the Gas Stream
Authors: Ocampo Alonso , Restrepo Alejandro , Clavijo Julian , Mejía Juan M.
Published: August 2020

This work presents the concept, progression, execution and results for a successful field implementation for a new technique to create insitu blocking foams in a gas condensate naturally fractured reservoir by the injection of the foaming agent dispersed in the hydrocarbon gas stream. This new technique aims at simplifying the operation and reducing the footprint and costs for the deployment of EOR foams in gas injection based projects. It also helps to overcome the disadvantage of limited reservoir volume of influence obtained by the SAG technique.

The selected field area for the pilot was confirmed to be naturally fractured dominated both by the production and gas injection performance. The field area had only one oil producer and one gas injector, so monitoring the results of the pilot was simplified. The operation was carefully planned so that a ramp up in foamer solution concentration could be implemented at the field, and the response of the gas injector well could be monitored in real time. Additionally, a gas tracer program was implemented to track the fly times of the gas prior and after the dispersed foam treatment.

About 1000 Bbls of foaming solution were dispersed in the hydrocarbon gas stream in one gas injector of a gas condensate Piedemonte field, whose injectivity performance was confirmed to be highly influenced by the natural fractures. Base gas injection conditions were about 30 MM scfd at 3800 psi WHIP. Once the dispersed foamer injection started, the gas injectivity in the well was progressively reduced to the point of increasing the WHIP to ~5000 psi, and the final gas rate was half of the base. The oil production well influenced by this injector changed its performance showing an increasing ramp in oil production and a reduction of the gas oil ratio (GOR) after the dispersed chemical injection period. The tracking of the gas tracers evidenced a delay in the gas fly times between the injector and the producer wells of two fold (63 days Vs 28 days), as a consequence of the dispersed foam treatment.

This is the first time a successful foam EOR field pilot is done in a naturally fractured reservoir by the injection of the foaming agent dispersed in a hydrocarbon gas stream. It is believed this new foams technique could also be extended to other non-condensable gases at field operating conditions like CO2, Nitrogen, Air, and Flue Gas.