bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formation Lithology Classification: Insights into Machine Learning Methods
Authors: Mohamed Ibrahim Mohamed , Mohamed Salah , Mazher Ibrahim , Chester Pieprzica 
Published: September 2019

Abstract
With the recent tremendous development in algorithms, computations power and availability of the enormous amount of data, the implementation of machine learning approach has spurred the interest in oil and gas industry and brings the data science and analytics into the forefront of our future energy. The idea of using automated algorithms to determine the rock facies is not new. However, the recent advancement in machine learning methods encourages to further research and revisit the supervised classification tasks, discuss the methodological limits and further improve machine learning approach and classification algorithms in rock facies classification from well-logging measurements. This paper demonstrates training different machine learning algorithms to classify and predict the geological facies using well logs data. Previous and recent research was done using supervised learning to predict the geological facies.
This paper compares the results from the supervised learning algorithms, unsupervised learning algorithms as well as a neural network machine learning algorithm. We further propose an integrated approach to dataset processing and feature selection. The well logs data used in this paper are for wells in the Anadarko Basin, Kansas. The dataset is divided into training, testing and evaluating wells used for testing the model. The objective is to evaluate the algorithms and limitations of each algorithm. We speculate that a simple supervised learning algorithm can yield score higher than neural network algorithm depending on the model parameter selected. Analysis for the parameter selection was done for all the models, and the optimum parameter was used for the corresponding classifier.
Our proposed neural network algorithm results score slightly higher than the supervised learning classifiers when evaluated with the cross-validation test data. It is concluded that it is important to calculate the accuracy within the adjacent layers as there are no definite boundaries between the layers. Our results indicate that calculating the accuracy of prediction with taking account the adjacent layers, yield higher accuracy than calculating accuracy within each point. The proposed feed-forward neural network classifier trains using backpropagation (gradient descent) provides accuracy within adjacent layers of 88%. Our integrated approach of data processing along with the neural network classifier provides more satisfactory results for the classification and prediction problem. Our finding indicates that utilizing simple supervised learning with an optimum model parameter yield comparable scores as a complex neural network classifier.
Hydrodynamics, Geothermics and Spatial Variations in Hydrocarbon Fluid Distribution within the Montney Formation, Alberta and British Columbia, Canada
Authors: Gibbs Allison , Rakhit Kaush 
Published: September 2019

Abstract
Hydrodynamics and geothermics are important tools for understanding the complex distribution of reservoir fluids in the Montney Formation in Alberta and British Columbia, Canada. The Montney comprises a conventional system in the east and an unconventional, Deep Basin-style hydrocarbon system in the west, where an underpressured, oil-dominated fairway just west and downdip of the conventional system grades further downdip into overpressured liquids and gas fairways.
The first part of this study addresses how these systems can be mapped from a pressure and temperature perspective. The Montney hydrodynamics system is explained using pressure versus elevation graphs. Key contours are taken from pressure-depth ratio maps to define the general boundaries between systems, noting that these boundaries change with depth. Geothermal gradient mapping is used to identify areas of prominent high or low geothermal gradients, which can have a significant effect on the positioning of gas liquids fairways. Key current day isotherms are also identified to represent the current phase windows by relating present-day formation temperatures to Tmax data.
To evaluate how pressure and temperature affect liquids production within the Montney, liquids production trends need to be considered. The second half of the paper discusses how mapping gas composition, particularly C2+ Wet Gas Index (WGI), may serve as a good proxy for liquids yields.
While the authors appreciate the complexities of phase behavior and the various factors influencing liquids production, the objective of this paper is to link trends that can be observed in liquids production to trends in pressure, temperature and gas composition. Ultimately, this paper examines ways in which hydrodynamics and geothermics can be used to help predict spatial variations in observed liquids production. By analyzing the co-relationships of the pressure, temperature and WGI data, the Montney segregates into two distinct domains which we term the Northern (British Columbia) Play and the Southern (Alberta) Play. This analysis can be tied in with other data sets for a better understanding of the reservoir such as: isotope geochemistry to gain insights into hydrocarbon migration; Special Core Analysis (SCAL) data to gain insights into fluid mobility; vapour-liquid equilibrium data to examine hydrocarbon fractionation during production; and completions data to provide a more complete picture of reservoir deliverability.
Dielectric Constant Interpretation: Comparison of the Salinity Dependence of the Real and Imaginary Response
Authors: Myers Michael 
Published: September 2019

Abstract
In this paper the dielectric constant of shaly sands both the real and imaginary parts is investigated and compared. An empirical model has been developed in the one MHz to one GHz frequency range for the real part of the dielectric constant. The equations developed involve the same pore systems as those governing the conductivity response. The dielectric constant contains an additionalfrequency independent high frequency limit. The dispersive terms are due to the clays and interfacial phenomena. The salinity and frequency dependence of these parameters are then discussed.
This salinity dependence of the dielectric model is compared to the salinity dependence both predicted and measured for the conductivity. Conductive inclusions are modeled similar to previously published work (Myers 1989) The Hanai-Bruggeman equation plays the central role which is consistent with Archie's equation but allows for conductive inclusions. The model for dispersed clays incorporates the effects of clay geometry and demonstrates that the conductivity is intimately related to the geometry and length scales involved in the clay conduction. The increase in the effective clay-counter ion mobility with increasing salinity is due to the coupling between the conductivity of the clays and the conductivity of the brine. It also demonstrates that the shape of the conductivity curve depends on the ratio of intergranular to clay porosity.
Effectiveness Study of the Spectral Approach to Geostatistical Simulation
Authors: Ismagilov Niyaz , Popova Oksana , Trushin Artemii 
Published: September 2019

Abstract
The spectral simulation approach is a recently developed geostatistical method of stochastic reservoir property simulation. The method has theoretical advantages over classical methods and the present work studies its practical effectiveness applied to synthetic data and real case of oil reservoirs. The study provides analysis of simulations results and describes strengths and limitations of the spectral method as well as application domain where it is most efficient.
The spectral method is based on Fourier analysis of well log data and consists of three major steps: decomposition of the well logs into Fourier series, simulation of Fourier coefficients in the interwell space and reconstruction of synthetic logs at every lateral point as sum of the Fourier series. The method was implemented in a software application and was used by authors for simulation of three-dimensional reservoir properties.
The effectiveness of the spectral method was studied based on simulations of continuous variables on a synthetic model. Simulations performed by the spectral method were compared to simulation results obtained on the same data by the more traditional method of sequential Gaussian simulation (SGS) provided by a commercial software. Analysis of the results from quantitative and qualitative points of view showed that the spectral method performed better at reproducing vertical non-stationarities observed in well data.
Practical applicability of the spectral method was demonstrated by simulation of porosity on a real oil field model, characterized by increase of porosity along depth with higher values of porosity closer to the bottom of the simulated layer. It was shown that the spectral method handled better this type of heterogeneity and reproduced distribution of porosity along the vertical axis closer to that of well data.
Promising Pathways to Lower Atmospheric Carbon Without Sacrificing the Petroleum Advantage
Authors: Gupta Subodh Chandra 
Published: September 2019

Abstract
The traditional advantage of petroleum-based transport fuels of unmatched energy-density and affordability is diluted with the requirement to lower atmospheric carbon. However, despite a significant R&D effort and investment over the last three decades, humanity is still looking for carbon neutral alternatives to petroleum that can be commercially viable. This paper presents meaningful novel approaches to deal with carbon abatement utilizing petroleum that have a better chance to succeed in fulfilling the underlying techno-economic desirables.
While the multi-directional work performed in the past on the subject has informed us on a variety of related topics, going forward the society can benefit from a systematic approach to solving atmospheric CO2 problem building on the petroleum advantage. A framework formulating the challenge in terms of techno-economic and environmental requirements is presented that narrows down further work to only meaningful and promising leads. With this framework in mind a few specific pathways are proposed that naturally hold the desired traits if certain conditions are met. These conditions in turn define specific objectives of the subsequent developmental work. While it is premature to suggest any of these will develop into a commercially viable pragmatic method, due to the underlying criteria they hold a better chance to be successful. The presented pathways using advances in electro-chemistry, nanoscience, rational design, and other areas range from (a) mimicking natural fixation of CO2 as in plants to produce tailored polysaccharides or food, to (b) converting CO2 to substances such as carboxylic acids for easy and cost effective sequestration, to (c) changing the way petroleum fuel is used in internal combustion engines to alter the exit state of oxidation of carbon so that the waste product is easily and economically captured compared to the conventional waste product - CO2.
One outcome from the framework results in collapse of the economic models and associated technical approaches that aim to convert CO2 to sellable products, owing mainly to the volume of the global GHG challenge. On the other hand, a common element in the proposed promising leads is to deal with the problem of carbon abatement as an added step with an associated cost. The lower this cost, the less diluted the petroleum-advantage. In this context the framework also points to a range of relative costs that the carbon abatement approaches have to work within to retain the petroleum advantage.
The outlined technical approaches of carbon abatement are not previously discussed in the literature and hold the promise to help combat the global GHG challenge in a more practical and significant way.
Nanopaint-Aided Electromagnetic Pigging in Pipelines and Production Tubing
Authors: Wang Ningyu , Prodanovic Maša , Daigle Hugh 
Published: September 2019

Abstract
Precipitation and deposition of paraffin wax and hydrates is a major concern for hydrocarbon transport in pipelines, tiebacks, and other production tubing in cold environments. Traditionally, chemical, mechanical, and thermal methods are used to mitigate the deposition at the expense of production interruption, complex maintenance, costs, and environmental hazards.
This paper studies the potential of nanopaint-aided electromagnetic pigging. This process has potentially low production impact, simple maintenance, low energy cost, and no chemical expense or hazards. The electromagnetic pig contains an induction coil that emits an alternating magnetic field. The alternating magnetic field induces heat in the nanopaint coating (i.e. coating with embedded paramagnetic nanoparticles) on the pipeline's inner wall and in the pipeline wall itself. The heat then melts and peels off the wax and hydrates adhering to the pipeline, allowing the hydrocarbon to carry them away.
We analyze the heating effectiveness and efficiency of electromagnetic pigging. The heating effectiveness is measured by the maximum pigging speed that allows deposit removal. The heating efficiency is measured by the ratio of the heat received by the wax over the total emitted electromagnetic energy, which we define as the pig induction factor.
Based on our numerical model, we compare the pig induction factor for different coil designs, different hydrocarbon flow rates, and different pig traveling speeds. We find that slower pig speed generally improves the pigging performance, that shorter solenoids with larger radius have higher efficiency, and that the oil flow does not considerably affect the process. We re-evaluate the maximum pig speed defined by the static pig model and confirm that a solenoid with larger radius allows higher pig speed.
We investigate the potential of a novel, low-maintenance electromagnetic pigging method that poses minimal interruption to production. This investigation is a basis for a new technology that stems from initial experimental investigation done by our collaborators. We here provide parameters for pig design and pigging protocol optimization, and will put them in practice in our future lab experiments.
Mobilizing Tight Matrix Oil through CO2 Huff-N-Puff Method in a Fractured Sandstone Rock: A Case Study
Authors: Wei Bing , Zhang Xiang , Gao Ke , Li Yibo , Pu Wanfen 
Published: September 2019

Abstract
CO2 injection, either miscible or immiscible, has been recognized as a promising method to enhance oil production for tight reservoirs, with major projects in progress worldwide. This work targeted a tight sandstone reservoir in China, located in the Lucaogou formation of Jimsar sag, Junggar Basin. CO2 injection using huff-puff method was planned to stimulate the oil production because of the rapidly declining productivity of the existing horizontal wells. Although some laboratory works have been conducted for this site, there still lacks the knowledge of mobilizing process of the matrix oil when natural fractures are present. Herein, we present an experimental study of CO2 huff-n-puff in a fractured sandstone rock with the primary objective of elucidating the oil recovery dynamics in different phases under reservoir conditions. The results indicated that the oil recovery rate rapidly decreased with cycle numbers and CO2 huff-n-puff primarily recovered the oil in the large matrix pores. After three cycles, an incremential 32.2% of the original oil-in-place (OOIP) was produced. Based on the dynamics of oil mobilization, the main-determining-forces (MDFs) in this process were re-defined. CO2 displacement, CO2-oil interaction driven by diffusion, and depressurization dominated the first cycle, whereas from the second cycle the first two forces became insignificant. This implied that the soaking phase could be minimized or even eliminated from the second cycle in order to reduce the shut-in time in field application.
A Hybrid Modeling Approach to Production Control Optimization Using Dynamic Mode Decomposition
Authors: Zalavadia Hardikkumar , Sankaran Sathish , Kara Mustafa , Sun Wenyue , Gildin Eduardo 
Published: September 2019

Abstract
Model-based field development planning and optimization often require computationally intensive reservoir simulations, where the models need to be run several times in the context of input uncertainty or seeking optimal results. Reduced Order Modeling (ROM) methods are a class of techniques that are applied to reservoir simulation to reduce model complexity and speed up computations, especially for large scale or complex models that may be quite useful for such optimization problems. While intrusive ROM methods (such as proper orthogonal decomposition (POD) and its extensions, trajectory piece-wise linearization (TPWL), Discrete Empirical Interpolation Method (DEIM) etc.) have been proposed for application to reservoir simulation problems, these remain inaccessible or unusable for a large number of practical applications that use commercial simulators.
In this paper, we describe a novel application of a non-intrusive ROM method, namely dynamic mode decomposition (DMD). We specifically look at reducing the time complexity involved in well control optimization problem, using a variant of DMD called DMDc (DMD with control). We propose a workflow using a training dataset of the wells and predict the state solution (pressure and saturation) for a new set of bottomhole pressure profiles encountered during the optimization runs. We use a novel strategy to select the basis dimensions to prevent unstable solutions. Since the objective function of the optimization problem is usually based on fluid production profiles, we propose a strategy to predict the fluid production rates from the predicted states from DMDc using machine learning techniques. The features for this machine learning problem are designed based on the physics of fluid flow through well perforations, which result in very accurate rate predictions. We compare the proposed methodology using another variant of DMD called ioDMD (input-ouput DMD) for system identification to predict output production flow rates.
The methodology is demonstrated on a benchmark case and a Gulf of Mexico deepwater field that shows significant time reduction in production control optimization problem with about 30 – 40 times speedup using the proposed DMDc workflow as compared to fine scale simulations, while preserving the accuracy of the solutions. The proposed "non-intrusive" method in this paper to reduce model complexity can substantially increase the range of application of ROM methods for practical field development and reservoir management.
High-Resolution Ultrasonic Borehole Imaging Enhances Reservoir Evaluation in Oil-Based Muds
Authors: Li Peng , Lee Jonathan , Taher Ahmed , Coates Richard , Marlow Rodney 
Published: September 2019

Abstract
Obtaining high-resolution borehole images in oil-based mud (OBM) from logging-while-drilling (LWD) tools has been made possible through the recent development of ultrasonic imaging technologies. High-resolution acoustic impedance images enable reservoir evaluation through the identification of faults and fractures, bedding and laminations, and assessment of rock fabric. This paper presents examples of high-resolution images from a 4¾-in. ultrasonic imaging tool in OBM applications and discusses their value in assessing reservoir quality.
This paper provides details of field trials of an LWD ultrasonic imaging tool for use in boreholes ranging from 5¾ to 6¾ in. High-resolution images detailing both borehole caliper and acoustic impedance in both vertical and horizontal wellbores are shown, illustrating the high level of formation evaluation now available when OBM is used. The methodology used to address the impact of tool motion on the impedance images will also be covered. The value of real-time data on borehole stability assessment will be discussed, along with additional applications made possible from the real-time data, such as wellbore placement enhancement.
Both real-time and recorded data from field trials show the potential applications for the ultrasonic imaging tool. High-resolution impedance images covering different formations and lithologies show bedding planes and laminations and enable the calculation of stratigraphic dip, while the identification and assessment of fractures show the potential to aid operators during the development of their hydraulic fracturing program. Borehole caliper and shape assessment in real time can be used to modify the drilling parameters and to adjust mud weight, while providing an input into geomechanics assessment.
The LWD logs presented illustrate the factors that influence data quality and the methodology used to ensure high-resolution images are available in both vertical and high-angle wellbores using OBM. A direct comparison between data acquired while drilling and while re-logging sections is shown, highlighting the repeatability of the measurement while also illustrating the impact of time-since-drilled on the borehole. A comparison with wireline measurements highlights the potential for using the high-resolution LWD images as an alternative to wireline, where cost and risk of deploying the wireline may be high.
The ability to collect high-resolution images in OBM in wellbores ranging from 5¾ to 6¾ in. ensures that increased reservoir characterization is possible, leading to significant improvements in determining the viability of unconventional and other challenging reservoirs. The high-resolution amplitude images are comparable with those available on wireline technologies, and the real-time application of borehole size and shape for input into wellbore stability and geomechanics analysis ensures that common drilling hazards can be avoided.
High-Fidelity Transient Hydraulics Model for Well Construction
Authors: Amur Varadarajan Prasanna , Roguin Ghislain , Abolins Nick , Ringer Maurice 
Published: September 2019

Abstract
A mathematical model is developed to capture the dynamic features in the wellbore during drilling operations so that it could be used for real-time computations. The model comprises one-dimensional (1D) mud flow solvers, one for the drillpipe and the other for the wellbore annulus including the volume below the drill bit, integrated point models for the bell nipple, bottomhole assembly (BHA) nozzles, 1D shallow water model for the flowline, and point model for the bypass replicating the hydraulic circuit in the drilling rig. The model assumes compressibility of mud for the wellbore section along with its transient gel characteristics. The equations are solved using appropriate explicit numerical solvers and the results capturing the fast transients of the standpipe pressure, bottomhole equivalent circulating density (ECD), and the flow rates during dynamic drilling operations are presented to illustrate the performance of the model with field data.