bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating Human Factors into Petroleum Engineering's Curriculum: Essential Training for Students
Authors: Dadmohammadi Y. , Salehi S. , Kiran R. , Jeon J. , Kang Z. , Cokely E. T. , Ybarra V. 
Published: October 2017

Abstract
The contribution of Human Factors, in complex commercial and contractual environments like the oil and gas industry, is fully-fledged and admitted. With the understanding that there were cascading failures due to human errors, the root cause analysis of accidents reveals that many of them were preventable. The Human Factors has not been accentuated thoroughly in this industry, and, traditionally, the focus has been on personnel knowledge and competence. In addition, lack of emphasis on Human Factors in academia as a backbone of the industry could be another reason for this negligence. Therefore, the proper academic training, which thoroughly emphasizes the non-technical skills (NTSs) in conjunction with Human Factors, is lacking in the curriculum of complex engineering programs like petroleum.
For the first time, at the University of Oklahoma, the Human Factors in Oil and Gas Operations class was offered. The offered course fulfilled the mission of training petroleum engineering students to make an impact on oil and gas industry. In this class, the students were introduced to the required NTSs in the drilling operation. The course content was designed to include technical concepts in drilling such as well barriers' philosophy, challenges in well flow control, plugging and abandonment operation, and kick detection. Also, several NTSs include effective communication, decision-making, situational awareness, teamwork, individual and group scenarios based well control training. The course content reassures that young professionals gain applicable NTSs and carry them to their work environment asserting safe and environmentally sustainable operations. A novel training approach was offered to integrate the theories of Human Factors with NTSs through the virtual reality simulation experience. The state-of-the-art Virtual Reality Drilling Simulator (VRDS) facility coupled with a commercial drilling simulation software to facilitate the scenario-based training for students.
Novel Techniques and Completions for the Abandonment of Horizontal Wells
Authors: Mali Gwyn A. , Clark Travis M. , Barrett Mark A. , Tran Nhuan Quang 
Published: October 2017

Abstract
Horizontal wells are a regular feature of many oil and gas fields and pose different challenges to their vertical counterparts for the entire well life-cycle. A regularly overlooked element during well completion design is the preparation for ease of abandonment. Horizontal wells are often completed with slotted liners/gravel packs and in a toe-up configuration, and if required, the abandonment of these production sections can be a risky operation using standard abandonment tools and techniques.
This paper describes the execution and lessons learned of several horizontal well abandonment operations, including a novel abandonment procedure that overcomes many of the limitations of conventional abandonment procedures in the toe-up horizontal configuration. This novel technique involves the installation of tubing in the horizontal slotted liner, placing cement along the horizontal liner from the tip of the toe via an initial circulation operation, then subsequent perforation and packer squeeze operations to remediate any gaps in cement isolation.
The paper also shares the details of a recent completion design change implemented on several horizontal wells with slotted liners to enable simpler abandonments in the future. The completion change involves the installation of a series of blank pipe sections with swellable packers along the horizontal liner section. These sections will be used in the future to enable simple low-cost and effective cement squeeze procedures with coiled tubing units utilizing cement retainers or packers.
The novel procedure and completion changes described have become a new toolset for the safe and efficient abandonment of toe-up horizontal wells.
Quantification of Transportation of Deformable Gel Particles in Porous Media
Authors: Jing Wang , Hongling Zhang , Huiqing Liu , Wei Zhao , Haomin Liu , Chuanjin Yao , Jiapeng Zheng , Yinghao Shen 
Published: October 2017

Abstract
Channeling is a ticklish problem of water-flooding in mature reservoirs. Deep fluid diversion (DFD) using deformable gel particle (DGP) has shown promising conformance control and improvement of sweep efficiency for enhancing oil recovery. The transport behaviors of DGP including shearing, plugging, deformation, and breakage are significantly complicated. It is extremely different from percolation of fluid and sand-removal problems. Although some empirical models or knowledge have been reported in literature, there have been few quantitative investigations or mechanistic interpretations to such behaviors. Without a good understanding of these behaviors, reliable modeling and optimization of DGP treatment would be impossible. Therefore, quantification of DGP transport behaviors in porous media is extremely essential. In this paper, we first conducted a set of experiments to measure the characteristics of DGP passing through and the breakage using variable-diameter capillary. Then, the corresponding derivation of DGP passing through the throat was demonstrated based on the elastic mechanics theory. After that, experiments of DGPs transport in porous media were conducted to study the shearing behavior and plugging capacity for different scenarios. Finally, the oil displacement experiments of parallel sand cores with different permeabilities and viscosities were carried out using different DGPs to validate and apply the above quantitative achievements. The results show that the pressure gradient for DGP passing through exponentially increases as the diameter ratio of DGP to throat. It is also a function of elastic modulus, Poisson's ratio, the diameter ratio of DGP to throat, and friction coefficient according to the derivation. Moreover, the derived model has a good agreement with the experimental results. There is a critical diameter ratio of DGP to throat, above which the DGP will break under an enough pressure. Both resistance factor and sheared DGP diameter are the function of flow rate, the diameter ratio of DGP to throat, and initial diameter. The above models can be used to choose optimal DGP size and injection parameters for a certain scenario. The experimental results of oil displacement support the quantitative achievements very well. This work provides a solid mechanistic theory for modeling DGP flooding and offers a useful guidance to the design of DGP flooding in field applications.
Applying Systems Approach to Wells Process Safety Management for Hse Goal Zero Sustainbility
Authors: Dedenuola Adetola , Ogbuji Ikenna , Obanya Phillip , Ogedegbe Okurerie , Akhideno Mathias 
Published: October 2017

Abstract
This abstract highlights the strategic importance of Process Safety Management (PSM) to organizations, and introduces an innovative approach for assessing the robustness of a Process Safety Management System (PSMS), and for reengineering it as necessary to enhance and support sustainable performance in HSE Goal Zero (GZ).
Because process safety incidents occur mostly in operational activities, there is obvious temptation to treat Process Safety as an operational issue. But the huge loss (&gt;USD 60 billion fines/penalties and ~50% reduction of shareholder value) suffered by BP in the immediate aftermath of the Macondo Well Control Incident (WCI) revealed the strategic dimension of Wells Process Safety Incidents (WPSI), and their potential to precipitate corporate collapse if not properly mitigated against. Evidently, Wells Process Safety Management (WPSM) transcends operational level of organizational management and is quintessentially strategic due to the existential threats that failures in this area could pose to business survivability.
Consequently, it is imperative for organizations whose operations might involve Process Safety related Major Accident Hazards (MAH) to have a high-quality PSMS that is properly harmonized with their corporate strategic intent, goals and aspirations. However, the success or otherwise of this depends in no small measure on the robustness of the approach and methodology employed in developing the management system and testing its effectiveness on an ongoing basis.
A Semi-Analytical Model for Pressure Transient Analysis of Fractured Wells in Unconventional Plays with Arbitrarily Distributed Fracture Networks
Authors: Chen Zhiming , Liao Xinwei , Sepehrnoori Kamy , Yu Wei , Zhao Xiaoliang 
Published: October 2017

Abstract
In this paper, we present an efficiently semianalytical model for pressure transient analysis in fractured wells by considering arbitrarily distributed fracture networks. The semianalytical model included three domains: (1) matrix, (2) hydraulic fracture networks, and (3) discrete natural fractures. Using line source function, we developed the diffusivity equation for fluid flow in matrix. By applying the nodal analysis technique, we eliminated the flow interplay at fracture intersections and established the diffusivity equations for fluid flow in hydraulic fracture networks and isolated natural fractures. The pressure transient solution of these diffusivity equations was obtained by using Laplace transforms and Stehfest numerical inversion.
Results showed that with the discrete natural fractures, a "V-shaped" pressure derivative --the classical dual-porosity feature of naturally fractured reservoirs--emerged. With the hydraulic fracture networks, the reservoir system would exhibit pressure behaviors like "pseudo-boundary dominated flow", "fracture-interference flow", and "fluid-feed flow", etc. All these pressure characteristics were depending on the properties and geometries of natural/hydraulic fractures. In addition, through synthetic field application, we found that different (natural/hydraulic) fracture distributions and geometries had distinct behaviors of pressure derivatives, which may provide an effective tool to identify the properties of randomly distributed natural fractures as well as complex hydraulic fractures in unconventional plays.
Non-Equilibrium Solvent Injection Simulation via Pore Scale Heat Conduction and Dispersion
Authors: Bayestehparvin Bita , Ali S. M. , Abedi Jalal 
Published: October 2017

Abstract
In the mathematical treatment and numerical simulation of hybrid recovery processes, specifically SAGD (Steam-Assisted Gravity Drainage) with solvents, instantaneous phase equilibrium is assumed. Previous studies by the authors, and others, show that this is not the case. Experimental work and the lack of success in the field corroborate this view. In the present work, a non-equilibrium model is developed involving the solution of mass and heat transfer equations. The state of equilibrium is based on diffusion and dispersion at the pore scale.
First, a new model is developed for oil mobilization by solvent and heat based on diffusion and dispersion mechanisms for different solvents. The concentration distribution is used to calculate the partition coefficients in a gridblock based on temperature, pressure, composition, and apparent time. The latter is different from simulation time and is an indicator of gridblock interaction with the solvent. By defining new parameters viz. apparent time, a gridblock has a memory of how long it was in contact with the solvent.
The analytical model developed in the first phase of this work confirmed the need for a non-equilibrium model for reservoir simulation. The non-equilibrium partition coefficient developed for vapor solvents of methane, propane, and butane using compressible assumption for the vapor phase. The oil production appears to improve using a solvent if instantaneous equilibrium is assumed. In this study, the nonequilibrium approach developed for heated solvent showed the cumulative oil production decreased as a result of the inability of the solvent to reduce viscosity.
The present study is the first of its type in the development of a non-equilibrium pore-scale simulator. The outcome of this study is considered to be novel in reservoir simulation that can improve predictions significantly.
Impact of Pore Confinement on Production Behavior and GOR Profiles of Unconventional Reservoirs
Authors: Calisgan T. , Ozkan E. , Firincioglu T. , Sarak H. , Ozgen C. 
Published: October 2017

Abstract
This paper extends the discussion of the impact of pore-size distribution and connectivity on the productivity and GOR behavior of wells in unconventional reservoirs to more complex petrophysical heterogeneities and layered and compartmentalized systems. Two well congurations are considered: four vertical wells located at the corners of the grid and one horizontal well located in the middle layer of a three-layer system. A black-oil simulator, which includes the effects of capillary-pressure on phase behavior and gravity, is used in the study. Several simulation models are considered to investigate the impact of single-, dual-, and n-porosity formulations on oil and gas production profiles for different capillary-pressure distributions varying by layers or regions. Results accentuate the earlier conclusions that pore-size distribution and other petrophysical heterogeneities have a stronger effect than the magnitudes of the pore sizes on the productivity and GOR of unconventional wells.
Leak off Test LOT Modeling for Inclined and Horizontal Wells
Authors: Sun Kewen , Wu Lingyun , Bui Nghia , Samuel Robello 
Published: October 2017

Abstract
Considerable efforts have been devoted to the modeling of the results for the Leak-off Tests (LOT) in the past. Over the last decade, there are two major focuses in this field of research: the extended application of LOT models to horizontal wells and the theory of the fluid leakage during LOT.
In the present study, an improved model has been proposed based on the original Altun's model: 1) the initial system volume is corrected after considering thermal and pressure effects as well as the geometry of the well path; 2) the casing expansion during LOT test is extended to directional wells with respect to pressure change; 3) a new leak volume model is developed to analyze the different flow behavior of fluid before and after the fracture initiation pressure (FIP). The data from a field example is used to validate the model. The predicted results demonstrate the improvement and accuracy of the model for the estimation of LOT values for horizontal wells.
From Face Detection to Fractured Reservoir Characterization: Big Data Analytics for Restimulation Candidate Selection
Authors: Udegbe Egbadon , Morgan Eugene , Srinivasan Sanjay 
Published: October 2017

Abstract
In recent years, there has been a proliferation of massive subsurface data from instrumented wells. This places significant challenges on traditional production data analysis methods for extracting useful information, in support of reservoir management and decision-making. Additionally, with increased exploration interest in unconventional shale gas reservoirs, there is a heightened need for improved techniques and technologies to enhance understanding of induced and natural fracture characteristics in the subsurface, as well as their associated impacts on fluid flow and transport.
The above challenges have the potential to be addressed by developing Big Data analytic tools that focus on uncovering masked trends related to fracture properties from large volumes of subsurface data, through the application of pattern recognition techniques. We present a new framework for fast and robust production data classification, which is adapted from a real-time face detection algorithm. This is achieved by generalizing production data as vectorized 1-D images with pixel values indicating rate magnitudes. Using simulated shale gas production data, we train a boosted binary classification algorithm which is capable of providing probabilistic predictions. We demonstrate the viability of this approach for identifying hydraulically fractured wells which have the potential to benefit from restimulation treatment. The results show significant improvements over existing type-curve based approaches for recognizing favorable candidate wells, using solely gas rate profiles.
Fully Dissolvable Fracturing Plug for Low-Temperature Wellbores
Authors: Fripp Michael , Walton Zachary , Norman Tyler 
Published: October 2017

Abstract
Dissolvable fracturing plugs are used for hydraulic fracturing applications. However, most new dissolvable materials have slow or no degradation in low-temperature formations. A new low-temperature dissolvable fracturing plug was developed for low-temperature formations. This new dissolvable fracturing plug is composed of a high-strength metal with elastomeric seals that dissolves completely in lower-temperature wellbore fluids.
Traditional fracturing plugs are constructed from composite materials and nondissolving elastomers. These nondissolving fracturing plugs obstruct production and need to be milled out after fracturing is completed. Dissolvable fracturing plugs dissolve in wellbore fluid, eliminating the need for a separate mill run intervention into the wellbore. However, the dissolution process slows in lower-temperature shale formations and the elastomer often ceases degradation at these lower temperatures. Therefore, a new metal and elastomer was developed that allows for the complete dissolution of the fracturing plug in lower-temperature formations.
The new low-temperature fracturing plug is optimized for use with the fluids used and temperatures experienced in the Marcellus and Permian basins. Comprehensive laboratory testing was conducted on the dissolvable metal alloy and dissolvable elastomer for the new low-temperature dissolvable fracturing plug. The dissolvable metal alloy is a metallic alloy that is combined with a dopant. Metallographic analysis illustrates the effect of the dopant on the dissolution of the metallic alloy and the accelerated dissolution needed for lower-temperature formations. The dissolvable elastomer uses a hydrolytic degradation reaction that is accelerated for low-temperature fluids. The result is a high-strength fracturing plug that can be set anywhere within the wellbore and will dissolve completely at formation temperatures between 120 and 180°F. The high-strength dissolvable materials allow dissolution in water-based wellbore fluid, formation fluid, or production fluid.
The novel fracturing plug is designed for low-temperature plug-and-perf applications and is composed of a new high-strength engineered metal and elastomer. Complete dissolution of the fracturing plug eliminates the need for a separate mill run intervention into the wellbore, which helps reduce costs, operation time, and risks to personnel. This paper discusses the development of the dissolvable metal, the development of the dissolvable elastomer, and the tested behavior of the low-temperature dissolvable fracturing plug.
Stop, Drop and Circulate; An Engineered Approach to Coiled Tubing Drillouts
Authors: Pope Charles , Charlton Alistair , Inscore Josh , Epperson Ryan , Sumner Blaine 
Published: October 2017

Abstract
In 2015, Devon Energy spent $60 million on post-stimulation drillouts. The average cost of a drillout was $250,000 when no issues were encountered. However, drillouts with significant issues cost an average of $1.7 million. In November 2015, the Drillout Group (DOGs) was formed to study and find solutions for issues associated with coiled tubing drillouts. The team consisted of 15 completions and drilling engineers directly involved in coiled tubing drillouts. The team met for eight months and invested more than 1,000 hours of engineering time. The DOGs visited with more than a dozen vendors, took three field trips and conducted laboratory experiments on various fluid systems.
This paper examines the history of coiled tubing drillouts at the operator and how stuck events were considered to be a normal aspect of operations. The DOGs team was tasked with engineering a solution to coiled tubing drillouts and formulating a Best Practice (BP) to apply companywide to minimize "train wrecks." The primary focus of the DOG team was to create standards for coiled tubing jobs including the target Reynolds numbers, annular velocity, chemicals, viscosities, torque and drag, early warning signs and corrective actions to prevent stuck pipe.
The paper evaluates the implementation of a real-time monitoring station and the results from 50 wells drilled out following the DOG best practice. The new best practice and live monitoring station resulted in average savings of $100,000 and average drillout time of 21 hours per well with zero stuck or sticky events recorded.
A Machine Learning Approach to Optimize Shale Gas Supply Chain Networks
Authors: Asala H. I. , Chebeir J. , Zhu W. , Gupta I. , Taleghani A. Dahi , Romagnoli J. 
Published: October 2017

Abstract
The unsteady recovery of oil and gas prices in early 2017 led to an increase in drilling and hydraulic fracturing operations in North America liquid-rich shale plays. The increasing number of producing wells, in addition to re-fractured wells, impose the need for optimizing field development strategies and shale gas supply chain networks that maximize profitability. Moreover, operators must account for undulating natural gas demands both locally and externally in a persistently low oil price environment. In this paper, we adopt supervised machine learning approaches to forecast local natural gas demand as well as guide well re-frac candidature. Both serve as critical inputs for maximizing the net present value of any shale gas field development project. An optimized water management structure is also incorporated in the proposed framework to account for associated produced-water recycling.
Considering a shale gas network in the Marcellus play, supply chain optimization was achieved using a mixed integer non-linear programming formulation. The Strategic Planning model relies on at least 4 major efforts including reservoir simulation, which in turn relies on output from a feed forward Neural Network (NN) algorithm. The trained NN algorithm was deemed suitable for recommending re-frac candidates, necessary decision variables for multiphase reservoir simulation. Finally, NPV optimization relied on a four-layer Long Short-Term Memory (LSTM) recurrent neural network, developed for forecasting local shale gas demand. Both neural network algorithms were scripted using python.
17 non-redundant parameters were mined for 250 wells in the case study. The t-Distributed Stochastic Neighbor Embedding technique was used to visualize related low dimensional manifolds within the high-dimensional data set, and a NN algorithm was used to obtain probabilities of misclassification. The well-pads in the case study superstructure are modeled using compositional reservoir simulation. Each reservoir model is tuned by history matching production and pressure data for designated producing wells. Alternative field development strategies (including re-fracturing) are then simulated for a 10-year planning horizon to generate gas and water rate decline profiles. Using the LSTM developed, local gas demand is forecasted using data sets created from multivariate time-dependent local and global variables affecting shale gas demand. The LSTM algorithm is derived by convolving some features from the raw data set, with fined-tuned weights, with the objective of minimizing a pre-defined demand error function. The results obtained show that application of this integrated approach can give operators a calculated advantage, preventing erroneous feedback of project profitability but allowing early time decision-making that maximizes shale asset NPV.