bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Unique Approach to Comply with the New Source Performance Standards NSPS for Methane Emissions for Hydrocarbon Producing Wells
Authors: Smith Steve , Denney Tommy 
Published: March 2017

Abstract
For decades, downstream hydrocarbon production facilities have been faced with compliance with the EPA Leak Detection and Repair (LDAR) fugitive emissions program. Now the upstream business must comply with the New Source Performance Standards (NSPS) for VOC emissions for the oil and natural gas industry per EPA's proposed rules that would require that the industry reduce methane emissions. Specifically, the EPA intends on reducing fugitive methane and VOC emissions from new and modified oil and natural gas production well sites.
Wellhead Emissions Management Systems, LLC of Houston, Texas has a developed a patent pending approach for the remediation of Methane and VOC emissions for gas production wellheads at a significantly lower cost than currently estimated by the EPA. Per the EPA - Regulatory Analysis Engineering Compliance Cost Estimates, the second most expensive item to comply with under the proposed regulation is fugitive emissions. The 2020 capital cost of compliance is estimated to range from $15MUSD to $22M increasing to $95M to $140M by 2025. The annualized cost of compliance is estimated to be between $29M and $47M swelling to $180M to $290M by 2025. Additional annual cost compliance estimates developed by the EPA state the cost to control wellhead fugitive emissions to be $310MUSD or $2,237 per well per year. Industry estimates for compliance have placed the cost at 0.65 cents per 1,000 SCF of gas produced. The containment and remediation system currently in field testing by Wellhead Emissions Management Systems, LLC expects to reduce the annualized cost by 30% per wellhead, while at the same time eliminating the need for immediate maintenance on wellheads when emission levels exceed the EPA NSPS allowable levels.
Deploying Human Performance: Where Do We Start?
Authors: Cook Matt 
Published: March 2017

Abstract
This paper shares Chevron's human performance initiative, and the role human performance plays in reducing serious incidents and fatalities. The paper defines what human performance is at Chevron, and how it is being integrated in the organization at the local and corporate levels. The gap analysis and prioritization tool (GAAP) has been developed to provide snapshots of the culture throughout a local organization and provide local leadership with specific actions to include in their integration planning. The GAAP takes the complex task of integrating human performance and targets areas where human performance can have the greatest impact.
The GAAP is made up of 19 statements derived from the United Kingdom (UK) Health and Safety Executive (HSE) Human Factors Inspector Toolkit and the Step Change in Safety Human Factors Toolkit. The statements describe attributes of an integrated human performance organization and include statements from each of Chevron's human performance focus areas: leadership engagement; incident investigation, reporting and learning; managing safe work; process safety; human factors engineering; and physical and psychological well-being. The GAAP is administered in facilitated small group discussions at varying levels throughout an organization (i.e. operations, front-line supervisors and leadership).
Participants in the discussion are asked to compare the GAAP statement against their current perspective of the organization and provide a ranking for each statement based on level of implementation. During the ranking process participants are asked to justify their ranking and provide examples where applicable. Comments and rankings are captured by a facilitator who analyzes the raw data and comments to identify themes and opportunities for the organization. The feedback is presented to the organization's leadership along with a recommendation of where to apply specific human performance tools and solutions based on the GAAP responses and data.
Results from the GAAP have proven to be valuable at the local and enterprise levels. At the local level, the feedback allows the organization to identify low hanging fruit and provide specific inputs into the organization's integration plan. At the enterprise level the information has help shape the corporate strategy and influenced the next steps along the human performance initiative for Chevron.
Technology and Innovation For Environmental Monitoring on Alaska's North Slope
Authors: Febbo E. , Payne K. , Reep B. 
Published: March 2017

Abstract
Alaska's North Slope is a unique environment, located above the Arctic Circle. Despite harsh weather conditions and logistical challenges, oil and gas development has been a part of this environment for many decades and environmental management and monitoring continues to be a significant aspect of development and operating facilities. Several innovative approaches to environmental monitoring will be highlighted, including early detection of polar bears using radar, caribou monitoring using satellites, and vegetation and hydrology monitoring using unmanned aerial systems (UAS).
Environmental Concerns and Quality of Life Following the Gulf Oil Spill: Factors Contributing to Behavioral Health
Authors: Osofsky Howard , Hansel Tonya Cross , Speier Anthony , Osofsky Joy , Savage Nicole 
Published: March 2017

Abstract

Objectives/Scope
An individual's connection to their environment is evident in Southeastern Louisiana, as this area represents a major economic hub for the United States port, petroleum, and fishing industries. The location also exposes the population to both natural and technological disasters that impact life on many levels, with residents' behavioral health being particularly vulnerable. Areas situated along the Gulf Coast are repeatedly experiencing and recovering from disasters with efforts to improve both preparedness and response being much needed. Specifically we need to improve our understanding of behavioral health factors, both positive and negative, that influence disaster recovery. There is an increasing amount of literature on negative health risks following disaster exposure, however little is known about how connection to one's environment and resilience contribute to or protect against negative behavioral health effects.

Methods, Procedures, Process
To better understand how both risk and protective factors contributing to post disaster behavioral health effects, this study assessed the association among environmental quality of life, environmental concerns, resilience, disaster experiences, and mental health symptoms. A total of 859 residents that reported some impact from the Gulf Oil Spill and lived along the Louisiana Gulf Coast were sampled. Structural Equation Modeling techniques were used to test the association among factors predicting mental health.

Results, Observations, Conclusions
The overall model demonstrated acceptable fit and disaster experiences were predictive of both environmental quality of life and mental health. Environmental quality of life was predictive of resilience and environmental quality of life and resilience were predictive of mental health.

Novel/Additive Information
This study found that disaster experiences were an important contributor, not only to one's post disaster mental health, but also to one's perceived environmental quality of life. Importantly environmental quality of life contributed to resilience or the perceived ability to overcome challenges. These findings can assist with development of post disaster recovery community response efforts that build on underutilized strengths, such as resilience and enhanced environmental quality of life.
History Matching of Reservoirs by Updating Fault Properties Using 4D Seismic Results and Ensemble Kalman Filter
Authors: Etienam Clement , Mahmood Intesar , Villegas Rossmary 
Published: March 2017

Abstract
This work focuses on the improvement of an integrated methodology for the automatic history matching of compartmentalised reservoirs using 4D seismic results, stochastic initialization and the Ensemble Kalman Filter method. We show the comparison of two different history matching approaches using the Ensemble Kalman Filter (EnKF) to update the Fault Transmissibility Multipliers (FTM) initially estimated with and without considering the 4D seismic results. In this study, the parameters updated during the history matching are two-phase fault transmissibility multipliers (FTM), absolute permeability and effective porosity of a synthetic realistic 3D reservoir. The true impedance map and the changes in reservoir pressure and saturation were previously computed from 4D seismic results. The systematic estimation of two-phase fault transmissibility multipliers is based on the integration of the collected 4D seismic results and an established method validated in our previous work based on a deterministic model, using the gradient-based History Matching, Levenberg Marquardt method (LM). We present the history matching of a synthetic reservoir using the Ensemble Kalman Filter (EnKF) considering the 4D seismic results to update the models and geostatistical techniques to produce the initial geological models. The stochastic method used is the Sequential Gaussian Simulation (SGS) technique to generate 100 initial models. During history matching using the EnKF, the saturation distributions are computed from the forward modelling of a two-phase system (oil-water). The impedance maps are then estimated using the Gassmann equation and compared with the true impedance map as part of the History Matching process. To validate the results, the cost function consisting of two components is calculated, the first is the structural similarity index of the two reconstructed impedance images to the real impedance image and the second is the RMS cost function value, l2 – norm of the difference between the true (real) and the simulated pressure-production data. The EnKF history matching using the two-phase FTM values considering 4D seismic results produced lower cost function values compared with the model using the initial FTM multiplier without considering 4D seismic results. The EnKF history matching algorithm using 4D seismic presented in this work produced results closer to the true reservoir impedance map compared to our previous 4D gradient based history matching method.
A Compositional Model for CO2 Storage in Deformable Organic-Rich Shales
Authors: Olorode O. M. , Akkutlu I. Y. , Efendiev Y. 
Published: March 2017

Abstract
Increased development of resource shales near industrial areas is spawning interests in storing CO2 generated from the neighboring industries in depleted organic-rich resource shales. This work presents a compositional model for the flow of a multi-component hydrocarbon gas and CO2 in a deformable porous medium consisting of an inorganic and an organic matrix. The fully-coupled equations for fluid transport and geomechanics are solved using the Control Volume Finite Element Method.
This work presents a mathematical model for CO2 storage in shales. The model accounts for the dispersed nature of kerogen in shale and can describe the advective and diffusive transport of the hydrocarbon components and CO2. The pressure- dependence of diffusion is modeled using the Maxwell-Stefan model, while desorption of the hydrocarbon species and adsorption of CO2 in kerogen is modeled with the Extended Langmuir Isotherm. The governing equations are solved implicitly for coupled geomechanics and flow. The developed simulator is used to model the primary depletion of a representative Barnett shale-gas reservoir, as well as the storage of CO2 in this depleted reservoir under various conditions.
The simulation results from this work indicate that the storage capacity of organic-rich shales could be overestimated if we do not account for the pore-volume reduction due to the pore space occupied by the adsorbed gas. During primary recovery from organic-rich shales, the pore-pressure drops and some of the gases adsorbed on the surface of the organic pore walls are produced. This results in an increase in the pore volume available for subsequent CO2 storage. However, the pore-pressure drop also results in an increased effective stress, which could lead to a reduction in fracture conductivity and cumulative production. The model and simulator presented is capable of modeling the relative contributions of these coupled phenomena and the attending effect on CO2 storage.
Chromatography Effects in Alkali Surfactant Polymer Flooding
Authors: Lüftenegger Markus , Clemens Torsten 
Published: March 2017

Abstract
Phase experiments were performed to determine an Alkali Surfactant Polymer solution leading to low interfacial tensions for oil produced from the 16 TH reservoir of the Matzen field in Austria.
Core flood experiments with the ASP solution were conducted to investigate the incremental oil recovery. Experimental data was history matched utilizing numerical simulation.
Results show that at laboratory scale, the various chemicals travel at different speeds owing to the different retardation. Owing to the short distance travelled, the location of the various chemical fronts is close together. Hence, the conditions in the core floods resemble the conditions in the phase experiments.
At reservoir scale, however, even after only 0.2 Pore Volumes (PV) injected, a significant separation of the species is seen. Owing to the difference of the reservoir and core scale, chemical compositions need to be used which are leading to sufficient incremental oil for a wide range of compositions. The incremental oil production from ASP flooding can be substantially overestimated if the separation of the chemicals owing to retardation is not accounted for in the design of the chemical flood.
In case that pseudo components are used in reservoir simulation, the components should have similar retardation characteristics to ensure that incremental recovery is not overestimated.
A Simultaneous Bayesian Estimation of Channelized Facies and Reservoir Properties under Prior Uncertainty
Authors: Zhao Yu , Forouzanfar Fahim 
Published: March 2017

Abstract
In this work, a Bayesian data assimilation methodology for simultaneous estimation of channelized facies and petrophysical properties (e.g., permeability fields) is explored. Based on the work of Zhao et al. (2016a,b), common basis DCT is used for the parameterization of facies fields in order to achieve model feature extraction and reduce the inverse problem dimensionality. An iterative ensemble smoother method along with a post-processing technique are employed to simultaneously update the parameterized facies model, i.e., DCT coefficients, and the permeability values within each facies in order to match the reservoir production data. Two synthetic examples are designed and investigated to evaluate the performance of the proposed history matching workflow under different types of prior uncertainty. One example is a 2D three-facies reservoir with sinuous channels and the other example involves a 3D three-facies five-layer reservoir with two different geological zones. The computational results indicate that the posterior realizations calibrated by the proposed workflow are able to correctly estimate the key geological features and permeability distributions of the true model with good data match results. It is known that the reliability of prior models is essential in solving dynamic inverse problems for subsurface characterization. However, the prior realizations are usually obtained using data from various sources with different level of uncertainty which results in great challenges in the history matching process. Thus in this paper, we investigate several particular cases regarding different prior uncertainties which include fluvial channels conditioned to uncertain hard data information or generated by diverse geological continuity models. The proposed methodology presents desirable robustness against these prior uncertainties that occur frequently in the practical applications.
Infill Well Portfolio Management under Uncertainty – Application to the 8 TH Reservoir, Austria
Authors: Sieberer Martin , Peisker Jörg , Clemens Torsten , Thiele Marco R. 
Published: March 2017

Abstract
The risk of economic failure of infill drilling campaigns increases with the increasing maturity of an oil field. The increased risk is due to the lower remaining movable oil in the late stages of a field's life compared to earlier phases. Despite the additional information owing to drilling of wells and production history, substantial geological and dynamic uncertainties remain. In this paper, an approach is presented for selecting an infill well portfolio of 10 wells from a total of 96 that explicitly accounts for these uncertainties.
The geological uncertainty can be exposed by generating a multitude of geological models conditioned to known log/correlation data. These models need to be classified and a subset of representative models extracted that in turn are calibrated (history matched) to past field performance and then used for forecasting. Calibration using a suitable ensemble of representative geological models aims to maintain geological diversity while reducing the error to historical data through an objective function.
Probabilistic Property Maps can then be generated to identify potential infill well locations. Probabilistic maps offer a major improvement compared to selection of infill well locations using a single geological realization. For mature assets, forecasting requires simulation of incremental oil recovery since infill wells represent incremental projects over a base case. Using an appropriate ensemble of models allows probabilistic representation of the incremental oil production and associated economics.
First, individual infill well performances are forecasted. Next, the individual infill well locations are evaluated taking the history matching error into account and using utility theory to cover the risk adverseness attitude of the company. Doing so enables selection of an infill well portfolio under uncertainty and leads to a selection of well locations carrying lower risk compared to a selection of locations neglecting history match error and/or disregarding the risk attitude of a company.
Effect of Injection Pattern Arrangements on Formation Connectivity During Water Flooding
Authors: Javaheri Parishad , Sadeghnejad Saeid 
Published: March 2017

Abstract
Water flooding is one of the most common methods during secondary recovery. The management of water injection can enhance the productivity of wells; whereas, the absence of proper supervision on injection can irreparably damage formations. Conventional approach to evaluate water flooding behavior is constructing a geological model, linking flow characteristics of the formation to the model, up-scaling it, and eventually running simulations so many times. The problem with this approach is that this method is computationally too expensive and time consuming. In addition, lots of data are required as an input. Therefore, there is a great interest to implement other physically based theories to quickly predict the performance of reservoirs when certain data are not available (e.g. during exploration phase). The percolation approach is one of these methods, which is based on the principal that a formation can be divided into two parts: permeable and impermeable medium. The percolation theory is a basic mathematical model for connectivity prediction in systems with complex geometries.
During water flooding, production and injection wells are normally drilled in a geometric configuration called flooding patterns. These well configurations enable us to attain an optimum production rate at the same time as to use the benefits of reservoir characteristics such as formation dip angle, faults, fractures, and permeability changes. The most common flooding patterns includes four-spot, five-spot, seven-spot, nine-spot, flat-linear pattern, and flat-fit pattern. The classic percolation approach uses two wells (i.e., injection and production wells) in a reservoir model. The effect of multiple wells in different configurations (i.e., injection well patterns) has not been investigated yet in the percolation literature. The main idea of this study is to implement an isotropic 2-D model within the framework of site percolation to determine the effect of water flooding patterns on percolation predictions. Square-shaped objects, representing formation sand bodies that contain hydrocarbon, are randomly distributed in the background of a formation by Monte Carlo simulations. The master curves of mean connectivity in a formation are then modeled by finite-size scaling laws for different injection patterns. All implemented codes are developed in C# language.
The results enable us to predict the connectivity of different water flooding patterns without any need for further detailed simulations. In addition, the percolation threshold as well as the connectivity exponent of different patterns is investigated in details. The implemented percolation-based model shows promising results that can be used when the conventional simulation-based approaches cannot be implemented due to uncertainty in input data.
Drilling Risk Migration Based on Borehole Failure Mechanism Analysis from Oil-Base Mud Images: A Case Study from West of Shetland, North Sea
Authors: Yang S. , Liu C. , Le Nir I. , Zhang T. , Bloemenkamp R. , Comparon L. 
Published: March 2017

Abstract
Drilling risk can be migrated based on borehole failure mechanism analysis, which provides valuable information for wellbore stability and formation damage protection. It is very challenging to identify the borehole failure in oilbase mud environment because of lacking of high resolution borehole image although we can get some information from cutting shape or sonic data with high uncertainty.
A new photorealistic micro-electrical imager for oil-based mud provides rich information on borehole failure and related formation damage from 3 different images (resistivity, permittivity and stand-off). The different borehole failure mode including tensile, compressional or shear are easily identified from resistivity or permittivity image.
The multiple arm radius data of this imager was also used to for borehole failure identification complementing with image feature interpretation. The special stand-off image was integrated for borehole failure identification as well.
One case study from Clair field, west of Shetlands North Sea was presented to demonstrate the borehole failure identification. The horizontal incipient breakout in horizontal well provides the consistent extensional stress regime; the breakout from vertical well show the new understanding of minimum horizontal stress and the mixture of drilling induced fracture and incipient breakout indicate the small ratio of two horizontal stress. The one dimensional mechanical earth model (MEM) of a horizontal well was updated based on borehole failure mechanism. The new MEM is more consistent with field leak of testing in other wells and provide valuable information for mud optimization to improve drilling efficiency in different risk intervals.
The new high-definition OBM-adapted micro-electrical imagesenabled confident identification and quantification of borehole tensile orshear failures and provides direct evidence for single well geomechanics earth model calibration.