bluuebunny/crossref_metadata_2025_split huggingface dataset:
Case Study: Optimizing Eagle Ford Field Development Through a Fully Integrated Workflow
Authors: Morales Adrian , Holman Robert , Nugent Drew , Wang Jingjing , Reece Zach , Madubuike Chinomso , Flores Santiago , Berndt Tyson , Nowaczewski Vincent , Cook Stephanie , Trumbo Amanda , Keng Rachel , Vallejo Julieta , Richard Rex 
Published: September 2019

Abstract
An integrated project can take many forms depending on available data. As simple as a horizontally isotropic model with estimated hydraulic fracture geometries used for simple approximations, to a large scale seismic to simulation workflow. Presented is a large-scale workflow designed to take into consideration a vast source of data.
In this study, the team investigates a development area in the Eagle Ford rich in data acquisition. We develop a robust workflow, taking into account field data acquisition (seismic, 4D seismic and chemical tracers), laboratory (geomechanical, geochemistry and PVT) measurements and correlations, petrophysical measurements (characterization, facies, electrical borehole image), real time field surveillance (microseismic, MTI, fracture hit prevention and mitigation program through pressure monitoring) and finally integrating all the components of a complex large scale project into a common simulation platform (seismic, geomodelling, hydraulic fracturing and reservoir simulation) which is used to run sensitivities.
The workflow developed and applied for this project can be scaled for projects of any size depending on the data available. After integrating data from various disciplines, the following primary drivers and reservoir understanding can be concluded. At a given oil price, optimum well spacing for a given completion strategy can be developed to maximize rate of return of the project. Many operators function in isolated teams with a genuine effort for collaboration, however genuine effort is not enough for a successful integrated modelling project, a dedicated multidisciplinary team is required.
We present what is to our knowledge, one of the most complete data sets used for an integrated modelling project to be presented to the public. The specific lessons from the project are applied to future Eagle Ford projects, while the overall workflow developed can be tailored and applied to any future field developments.
Permanent Storage of CO2 in Mexican Igneous Rocks
Authors: Cantú-Apodaca Erick , Ortiz-Lucas Pilar , Gómora-Figueroa Ana Paulina , Mancera-Alejández Javier , González-Torres Enrique 
Published: September 2019

Abstract
Mexico has undertaken a series of measures to implement Carbon Capture and Storage (CCS) technology due to the acquired national and international commitments regarding the reduction of GHG emissions as well as their implications to climate change. So far, the screening of the different methods for geological storage of CO2 potentially applicable in Mexico includes deep saline aquifers, non-economic coal beds, and crude oil reservoirs for EOR.
Storage of carbon dioxide projects in igneous rocks has been successful in the past. According to the literature, there are about eight sites, onshore, in the world with plenty of igneous rocks to store CO2, and Mexico is one of these sites. However, little attention has been paid to the study of igneous rocks as a potential method for geological storage of carbon dioxide.
This work aims the first petrographic and geochemical analysis to estimate the feasibility of CO2 mineralization thorough Mexican basaltic formations. This analysis includes the identification of the main CO2 emission areas in Mexico, the collection of samples near to large CO2 emissions sites and, the characterization of the samples by different tests and techniques. The properties of the rock samples and water were studied after the tests to compare changes in mineral phases and water composition.
The results herein confirm the feasibility of Mexican basalts to react in the presence of CO2 but also set the recommendations for the next steps to take to determine the technical feasibility of the CO2 permanent storage using basalts in Mexico.
Exploiting Shale Creep Deformation to Create Annular Barriers for Well Plugging and Abandonment: Experimental Investigation and Numerical Simulation
Authors: Enayatpour Saeid , Thombare Akshay , Aldin Munir , van Oort Eric 
Published: September 2019

Abstract
Oil and gas wells produce hydrocarbons for a limited number of years, and at the end of their production life they need to be plugged and abandoned. This process has to be done in a safe and economic way. Creep deformation of shale rock in uncemented casing sections may simplify well abandonments considerably. Creep can close the annular gap between a shale formation and an uncemented section of a casing string, generating a barrier that prevents hydrocarbons from flowing to the surface on the annular side. Wells with such a "shale-as-a-barrier" generated by creep now only require abandonment plugs on the inside of the casing, without the need for installation of additional annular barriers. This may eliminate such operations as casing milling and casing pulling, thereby allowing e.g. offshore abandonments to be done rigless, at significantly reduced cost.
This paper presents the first results of an experimental investigation and numerical modeling study into the nature of the "shale-as-a-barrier" phenomenon. Specifically, we focus on laboratory and field scale numerical simulation of creep behavior of North Sea Lark shale rock for oil and gas well plug and abandonment purposes. In our Finite Element simulations of the shale creep phenomenon, we have used the time-hardening creep model, which assumes a non-linear relationship between creep strain and stress, temperature and time. The model parameters were obtained from a curve fit of laboratory experimental results conducted for a creeping shale. Then, using the experimentally-derived parameters, numerical simulation was performed for a laboratory scale model and result was validated against laboratory results. Once this validation had taken place, the model size was extended to the field scale for prediction of annular closure time and barrier formation. Simulations show a strong correlation between rock stiffness and annular gap closure time, as expected; hence, the success of any "shale-as-a-barrier" project is a distinct function of shale rock stiffness. Lowering near-wellbore stiffness artificially may accelerate annular barrier creation of slowly creeping shale formations.
Methods for Late Life Solvent Recovery Enhancement in Thermal-Solvent Based in-Situ Recovery Processes.
Authors: Khaledi Rahman , Farshidi Forough , Motahhari Hamed Reza 
Published: September 2019

Abstract
Non-thermal-solvent and thermal-solvent based heavy oil recovery processes are technologies in which solvent is used as either the main or the secondary agent, in conjunction with heating, for bitumen viscosity reduction. In these processes a hydrocarbon solvent is injected into the reservoir and produced back with the recovered bitumen. A fraction of the injected solvent is retained in the reservoir at an equilibrium state as gas and liquid phases. Since the cost of injected solvent in these processes is a major portion of the operating cost, recovery of the retained solvent from the reservoir at the end of bitumen depletion stage results in recovery of significant capital and thus improvement of the process economics.
Imperial-ExxonMobil have been optimizing the existing and developing new recovery technologies to improve the efficiencies, economics and environmental performance of heavy oil production operations. Recent focus has been on developing solvent based recovery processes through an integrated research program that includes fundamental laboratory work, advanced numerical simulation studies, laboratory scaled physical modeling, and field piloting. The research program aims at in-depth investigation and understanding of process physics and mechanisms to allow evaluating and optimizing process performance.
In this paper, development of a new method for recovery of the retained solvent from the reservoir at the end of the bitumen depletion stage is introduced. This method takes advantages of solvent vapor-liquid thermodynamic equilibrium to strip the retained solvent from the reservoir. A stripping gas is injected and circulated in the bitumen depleted chamber to vaporize and recover the retained solvent to the surface. The reservoir modeling results show that this method is very effective and efficient in accelerating recovery of the retained solvent. The physical modeling experimental data confirms the effectiveness of this method. Field pilot data from a solvent assisted recovery process are presented which demonstrate solvent recovery efficiency using continuous steam injection.
A Utica Case Study: The Impact of Permeability Estimates on History Matching, Fracture Length, and Well Spacing
Authors: Fowler Garrett , McClure Mark , Cipolla Craig 
Published: September 2019

Abstract
Maximizing economic performance in shale requires optimal selection of well and cluster spacing, among other parameters. Reservoir engineering calculations can be used to optimize spacing, but these calculations are impacted by uncertainties in input parameters. System permeability is particularly important and difficult to measure. Diagnostic Fracture Injection Tests (DFIT's) are often used to estimate permeability because they provide a direct, in-situ measurement. However, in recent work, it was shown that conventional DFIT interpretation techniques can overestimate permeability in gas shale by two orders of magnitude. In this study, the impact of the permeability estimate is demonstrated using a dataset from the Utica/Point Pleasant. Production data is history matched with models assuming high and low permeability. It is possible to history match both models because of non-uniqueness between fracture area and permeability. Sensitivity analysis simulations are performed to assess the impact of well and cluster spacing on net present value. Relative to the high permeability model, the low permeability model has a greater optimal well spacing and a tighter optimal cluster spacing. The comparison shows that improved accuracy in the permeability estimate significantly improves economic performance. The low permeability model has much earlier production interference than the high permeability model because the low permeability model requires greater effective fracture length to match production. This is consistent with the operator's experience that outer wells outproduce inner wells within weeks or months from the start of production.
Use of Visualization Labs to Enhance Petroleum Engineering Education
Authors: Menouar Habib , Heinze Lloyd , Watson Marshall , Gamadi Talal 
Published: September 2019

Abstract
The quest for excellence and efficiency in academia and education is critical. Some of the best proven methods of assessing educational programs refer to the standards and approach developed by ABET (The Accreditation Board for Engineering and Technology). This institution which was initiated originally in the US is involved in the supervision and accreditation of more than 3750 educational programs spread internationally over 30 countries.
The Bob L. Herd Department of Petroleum Engineering has been using these standards since its ABET accreditation 66 years ago. It is still striving for excellence, improvement and perfection since then. The goal is to produce the best petroleum engineers using the last Student's Outcome approach (SO) and assessment methods as developed by ABET.
ABET approach uses various tools to assess educational programs, some of which are conventional such as: Examinations, quizzes, guided homework's, term projects etc. others are more involved. The data are translated into quantifiable parameters for analysis. In addition to all these tools, this study uses one more that has been proven to be valuable and added to the arsenal available at the Bob L. Herd DPE. It is the use of visualization labs. This consists of models built to simulate various forces, physical mechanisms and engineering concepts encountered in drilling, production and reservoir engineering. The present study is directed toward the use of petrophysical or scaled models to enhance the methods of education in petroleum engineering and more specifically in reservoir engineering. Scaled models are not new in the oil industry. They used to be the only way to study oil reservoirs and forecast their behavior until the advent of computers and numerical simulation in the 1970's.
Several scaled models designed to simulate water-flooding processes for educational purpose are used by students to complete projects on reservoir development. Analysis of the results shows the following: After completion of the projects, students have a better understanding of the fundamental concepts and principles behind reservoir engineering, depletion mechanisms and other issues related to fluid displacement in porous media.The Metrix associated with the student outcome and assessment methods developed for ABET evaluation showed that a well-conceived visualization lab can be extremely effective in petroleum engineering education in general and more particularly in reservoir engineering.
Reservoir Characterization-Geostatistical Modeling of the Paleocene Zelten Carbonate Reservoir. Case study: Meghil Field, Sirte Basin, Libya
Authors: Masaud Mohamed , Meddaugh W. Scott 
Published: September 2019

Abstract
Geostatistical-based models provide a considerable improvement for predictive reliability of dynamic models and the following reservoir management decisions. This study focuses on geostatistical modeling the Paleocene Zelten Carbonate reservoir in the Meghil field. The field was discovered in 1959 and production operations began in 1961. Nineteen wells have been drilled to date. The structural framework consists of three slightly asymmetrical anticlinal structures trending NW-SE with steeper dip on the SW flanks. Each of the structures are separated by major normal faults. Seismic interpretation suggests that carbonate build-ups are most likely present on the three separate structures. Edge detection was used to clarify the structural geometries and the presence of additional minor faults. Pillar gridding technique was used to develop the structural framework including four major faults that are partially sealed based on analysis of the available DST and production test data. Stratigraphic analysis indicates a local presentation of dolomitic limestone in the northern portion of the main and the western structures caused considerable litho-facies variation that impacted the distribution of the petrophysical properties. Basic and advanced formation evaluation the net reservoir thickness of about 15 feet with an average porosity of 17% and average water saturation of 35%. Geostatistical-based applications that combine the spatial statistics (e.g. the semivariogram) and the available well and core data were used to populate the reservoir model with porosity, permeability, facies (lithology), net/gross, and water saturation. A conceptual facies model was also used to constrain the reservoir property distributions. Sequential Gaussian Simulation (SGS) was used to populate the model with porosity and water saturation and Sequential Indicator Simulation (SIS) was used to populate the facies model with permeability. The modeling parameters (e.g. semivariogram, correlation coefficients) were significantly constrained by the limited number of wells. Based on the limited number of wells available the semivariogram analysis resulted in a spherical semivariogram model with major axis range of 1435 meters for porosity and 1800 meters for water saturation. Minor axis ranges were about 50% of the major axis ranges. Given the limited well data, a significant effort was made to document the potential impact of the semivariogram parameters on the original hydrocarbon in place (OHIP) estimates and the lateral stratigraphic continuity of reservoir properties. The deterministic approach resulted in place volume estimates of 60 MMBBL and the stochastic approach provided an estimate of 45 MMBBL.
Determination of Total Organic Carbon for Organic Rich Shale Reservoirs by Means of Cores and Logs
Authors: Xiong Hao , Wu Xiaye , Fu Jing 
Published: September 2019

Abstract
Oil production from shale and tight formations will increase to more than 6 million barrels per day (b/d) in the coming decade, making up most of total U.S. oil production (&gt; 50%). However, achieving an accurate formation evaluation of shale faces many complex challenges. One of the complexities is the accurate estimation of shale properties from well logs, which is initially designed for conventional reservoirs. When we use the well logs to obtain shale properties, they often cause some deviations. Therefore, in this work, we combine cores and well logs together to provide a more accurate guideline for estimation of total organic carbon, which is primarily of interest to petroleum geochemists and geologists.
Our work is based on Archie's equation. Resistivity log will lead to some incorrect results, such as total resistivity, when we follow the conventional interpretation procedure in well logs. Porosity is another complex parameter, which cannot be determined only by well log, i.e. density, NMR, and Neutron log. Therefore, the flowchart of TOC calculation includes five main parts: (I) the shale content calculation using Gamma log; (II) the determination of shale distributions using Density and Neutron logs and cross-plot; (III) the calculation of total resistivity at different distribution types; (IV) obtaining porosity using core analysis, NMR and density logs; and (V) the calculation of TOC from modified Archie's equation.
The results indicate that the shale content has a strong effect on estimation of water saturation and hydrocarbon saturation. Especially, the effect of shale content is exacerbated at a low water saturation. A more accurate flowchart for TOC calculation is established. Based on Archie's equation, we modify total resistivity and porosity by combining Gamma Log, Density Log, Neutron Log, NMR Log, and Cross-plot. An easier way to estimate porosity is provided. We combine the matrix density and kerogen density together and obtain them from core analysis. Poupon's et al. (1954) laminar model has some limitations when applying in shale reservoirs, especially at a low porosity.
Literature surveys show few studies on the flowchart of TOC calculation in shale reservoirs. This paper provides some insights into challenges of well logs, core analysis in shale reservoirs and a more accurate guideline of TOC calculation in shale reservoirs.
Integration of Time-Lapse Seismic Data Using the Onset Time Approach: The Impact of Seismic Survey Frequency
Authors: Liu Tian , Hetz Gill , Chen Hongquan , Datta-gupta Akhil 
Published: September 2019

Abstract
The seismic inversion method using the seismic onset times has shown great promise for integrating real- continuous seismic surveys for updating geologic models. However, due to the high cost of seismic surveys, such frequent seismic surveys are not commonly available. In this study, we focus on analyzing the impact of seismic survey frequency on the onset time approach, aiming to extend the advantages of onset time approach when infrequent seismic surveys are available.
To analyze the impact of seismic survey frequency on the onset time approach, first, we conduct a sensitivity analysis based on the frequent seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. The calculated onset time maps based on seismic survey data sampled at various time intervals from the frequent data sets are compared to examine the need and effectiveness of interpolation between surveys. Additionally, we compare the onset time inversion with the traditional seismic amplitude inversion and quantitatively investigate the nonlinearity and robustness for these two inversion methods.
The sensitivity analysis shows that using interpolation between seismic surveys to calculate the onset time an adequate onset time map can be extracted from the infrequent seismic surveys. This holds good as long as there are no changes in the underlying physical mechanisms during the interpolation period. A 2D waterflooding case demonstrates the necessity of interpolation for large time span between the seismic surveys and obtaining more accurate model update and efficient data misfit reduction during the inversion. The SPE Brugge benchmark case shows that the onset time inversion method obtains comparable permeability update as the traditional seismic amplitude inversion method while being much more efficient. This results from the significant data reduction achieved by integrating a single onset time map rather than multiple sets of amplitude maps. The onset time approach also achieves superior convergence performance resulting from its quasi-linear properties. It is found that the nonlinearity of the onset time method can be smaller than that of the amplitude inversion method by several orders of magnitude.
Prediction of Multilateral Inflow Control Valve Flow Performance Using Machine Learning
Authors: Aljubran Mohammad Jabs , Horne Roland 
Published: September 2019

Abstract
Intelligent multilateral well completions provide downhole flow rate, pressure, and temperature measurements at multiple well segments which allows for a continuous spatiotemporal data stream. Such an extensive data input poses a challenging task to decide on the optimal strategy of manipulating the inflow control valve (ICV) settings over time for best performance. This study investigated the use of machine learning to analyze and predict well performance given different ICV settings to ultimately maximize the well output.
A commercial reservoir simulator was used to generate two synthetic reservoir models: homogeneous (Case A) and heterogenous (Case B). These synthetic data were used to train, validate, and test machine learning models. The reservoir cases were generated based on a segmented, trilateral producer completed with three ICV devices installed at tie-in segments. The data used were measurements of wellhead and downhole flow rates across ICV segments over a period of 4,000 days. A total of 1,330 experiments were conducted with an eight-day timestep, generating a total of 667,660 sample data points for each of Case A and Case B. Fully connected neural networks were used to fit the data while model generalizability was enhanced using regularization techniques, namely L2 regularization and early stopping.
Both random sampling and Latin Hypercube Sampling (LHS) methods were evaluated in constructing the training, validation, and testing splits. Trained with different sample sizes drawn from the 1,330 simulated data histories for the two reservoir models, the proposed neural network showed excellent results. Given only ten simulated choices of ICV settings for training, the network proved capable of predicting oil and water production profiles at surface for both homogeneous and heterogeneous reservoir models with over 0.95 coefficient of determination (R2) when evaluated at unseen, test ICV settings. Extending the problem to downhole flow performance prediction, about 40 training simulated settings were necessary to achieve 0.95 R2. We observed that LHS was superior to random sampling in both R2 average and confidence interval. We also found that increasing the training and validation sample sizes increased the test R2 when testing against unseen cases. Study results suggest the applicability of machine reinforcement learning to estimate the well output at different ICV settings, where the neural network model depends fully on the real-time well feedback and production measurements.
By using a machine learning approach during the operation of a well with multiple ICV settings, it would be feasible to estimate the lateral-by-lateral output at unseen scenarios. Hence, it becomes possible to maximize the well output by using an optimization algorithm to determine the optimal ICV settings.