bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Approach for Optimizing Multistage Hydraulic Fracturing of Gas Condensate Horizontal Wells
Authors: Al-Garadi Karem , Aldughaither Abdulaziz , Ba alawi Mustafa , Al-Hashim Hasan , Sibaweihi Najmudeen , Said Mohamed 
Published: March 2019

Abstract
Condensate banking has been identified to cause significant drop in gas relative permeability and consequently reduction of the productivity of gas condensate wells. To overcome this problem, hydraulic fracturing has been used as a mean to minimize or eliminate this phenomenon. Furthermore multistage hydraulic fracturing techniques have been used to enhance the productivity of horizontal gas condensate wells especially in low permeability formation. Even though multistage hydraulic fracturing has provided an effective solution for condensate blockage to some extent as it promotes linear flow modes which will minimize the pressure drops and consequently improves the inflow performance considerably. However, this technique is very costly, and has to be optimized to get the best long-term performance of the multistage fractured horizontal gas condensate wells.
In this paper, multiple sensitivity analyses were conducted in order to come up with an optimum multistage hydraulic fracturing scenario. In these analyses, our manipulations were focused mainly on the operational parameters such as fractures half length, fractures conductivity using compositional commercial simulator. CMG-GEM simulator was used to investigate the different cases proposed for applying multistage hydraulic fracturing of horizontal gas condensate wells. The investigation began with a base case scenario where the fractures half-length were fixed for all stages with equal spacing between them. Then, six more fractures half-length patterns were created by introducing new approach where the well performance was studied if they are in increasing trend away from the wellbore (coning-up), or in a decreasing trend (coning-down). Well performance is furtherly addressed when the fractures half-length arrangements formed parabolic shapes including both occasions of concaving upward and downward. Finally, the last two patterns illustrated the effect of having the fractures half-length arrangements both skewed to the left and right on well productivity.
The investigation of the effect of changing the multistage hydraulic fractures half-length distribution patterns on the performance of a gas condensate well was conducted and resulted in parabolic up distribution pattern to be the optimum pattern amongst the other tested ones. It results in the highest cumulative both gas and condensate production. It also maintains the gas flow rate and bottom hole pressure more efficiently. The parabolic up distribution pattern confirms that the majority of gas production was fed by the fractures at the heel and at the toe of the horizontal drainhole which is in agreement with the flux distribution along the horizontal well.
Analysis of Sinusoidal Buckling of Drill String in Vertical Wells Using Finite Element Method
Authors: Cebeci Mehmet , Gücüyener ismail Hakki , Kök Mustafa Versan 
Published: March 2019

Abstract
The present work focuses on the stability of drill strings in vertical wellbores. The first rigorous treatment of stability of drill strings for vertical wellbores was presented by Lubinski (1950) and his equation is till most widely used in the industry. Cunha (2004) stated that since Lubinski (1950) used power series to solve differential equation governing the stability problem, and the terms of power series become very large for long drill strings, therefore, after a certain length, the calculations may lead to inaccurate results. Mitchell and Miska (2011) stated that analytical solution for infinite-length drill string is used for deep vertical wells in the industry. The subject studied in this study is of great importance in designing the bottom hole assemblies in deep and ultra-deep vertical wells to eliminate problems associated with instability of drill strings. The study includes Finite Element Method (FEM) solution of critical sinusoidal buckling force for 5 different drill collars with 21 different lengths starting from 1000 ft. up to 25000 ft. The main objectives of the study are to see the difference between post-buckling behavior of slender-dominated long hanging drill strings with stiffness-dominated short hanging drill strings in vertical wellbores; to investigate the effect of flexural rigidity of drill collars on decrease of the critical buckling forces as a length parameter of the drill string; and to see the behavior and amount of decrease in the critical buckling forces as the length of the drill string increases. And, it is showed that critical buckling force decreases as the depth of the well increases according to FEM solutions, although, analytical solution gives only a fixed critical buckling force for a specific pipe independent from the length. Also, it is showed that post-buckling behavior of slender-dominated long hanging drill strings with stiffness-dominated short hanging drill strings in vertical wellbores are different.
Phenomenology During Flowback in Unconventional Wells
Authors: Angulo Yznaga Reinaldo Jose , Quintero Luis Fernando , Negm Ehab , Van Laer Pierre 
Published: March 2019

Abstract
Flowback of wells after hydraulic fracturing has always been under debate because the future performance of fractured hydraulic wells depends on the operational procedure applied during the flowback. Unconventional reservoirs have become increasingly important hydrocarbon resources to develop and produce for the oil and gas industry, and the best cost-efficient approach to develop and produce unconventional reservoirs is by drilling and completion of horizontal multi-stage hydraulic fractured wells. Hence the complexity of the phenomenology seen during the flowback of this type of wells has increased substantially. The complexity of the phenomenology is the result of the change on the range of fluid and fluid-rock properties. The permeability of unconventional reservoirs is typically in the range of nano to low micro darcies. This implies that the forces acting on the fluid flow through the medium are extremely magnified. This paper is aimed at describing the phenomenology during early fluid flow in unconventional wells, and its relevance during the design, planning, and execution of well flowback.
The work considers actual data and information of flowback in unconventional wells from the available literature, as well as our own experiences. The authors use this available data and information to describe the physical phenomena that occurs in unconventional wells, especially in the early stages of production testing. The paper describes a theoretical approach that explains the fluid behaviour seen during multi-stage hydraulic fractured unconventional wells. Finally, the flowback is characterized based on the phenomenology, and its description provides an approach to an improved design of well flow management.
The characterization of the phenomenology during flowback allows us to identify six stages of fluid flow in unconventional wells during the early flow process. Each stage has been identified considering the acting forces, fluid flow, and implications during the flowback. After such description, flowback design is explained based on the phenomenology characterization. Finally, the authors provide a comparison of the design and the actual behaviour for the early stages of flowback.
This work introduces an approach based on the characterization of the phenomenology associated to multi-stage hydraulic fractured unconventional wells that have been successfully applied in flowback operations. A comparison between theoretical designs and actual cases confirms the value of the methodology.
Advanced Eor Foam in Naturally Fractured Carbonates Reservoirs : Optimal Balance Between Foam and Interfacial Tension Properties
Authors: Chevallier Eloïse , Bouquet Sarah , Gland Nicolas , Douarche Frédéric , Batôt Guillaume 
Published: March 2019

Abstract
In naturally fractured carbonate reservoirs, Gas Oil Gravity Drainage processes (GOGD) are successfully implemented but oil recovery is limited by a slow kinetics. However a gas EOR process represents a promising alternative to boost this oil production rate. Nevertheless the design of this process should address several technical challenges: the typically unfavorable wettability of the matrix (intermediate to strongly oil-wet), the densely connected fracture network and the high contrast of fracture-to-matrix permeability.
We propose here the injection of a advanced EOR foam with reduced interfacial tension. The foam flow in the fracture creates an important viscous drive leading to a pressure gradient, which increases the oil recovery dynamics compared to GOGD. Besides, the reduced interfacial tension (IFT) between crude oil and aqueous phase allows the aqueous phase to enter the matrix despite the unfavorable wettability.
In this paper, we demonstrate that a balance exist between IFT and foam strength performances to optimize the process. Three foam formulations are optimized with very different profiles in terms of IFT and foam performances. For their design, priority is given either to ultra-low IFT values (10-3mN/m) or to a strong foam with larger IFT (0.35mN/m) or to a balance between the two first formulations (0.03mN/m). Foams are evidenced as intrinsically less stable in ultra-low IFT conditions: apparent viscosity (in porous media) in contact with oil is respectively enhanced by a factor 40 when IFT rises from 10−3 to 10−1mN/m. Based on sandpack and coreflood experiments, we recommend an IFT in the order of 10−1 mN/mas a balance between the viscous drive in fracture and an efficient aqueous phase imbibition in the oil-wet matrix. Simulation work supports this experimental conclusion: the common target of IFT in the order of 10−3 mN/m determined by capillary desaturation curves in SP flooding can be adjusted to a higher IFT value, which can be deduced from the wettability of the reservoir.
To ensure an accelerated oil recovery in naturally fractured carbonate reservoirs, we recommend the design of a low-IFT foam formulation with revised IFT performances compared to a classical Surfactant-Polymer process targeting residual oil. Indeed, the final process is likely more efficient if the target of IFT is defined by wettability requirements rather than residual oil desaturation. This article gives the target formulation parameters which arise from the mechanisms at play (viscous drive and imbibition in oil-wet matrix), and are realistically achieved with industrial surfactants.
First Rigless Water Shutoff and Reservoir Cross-Flow Leak Mitigation Performed in the United Arab Emirates on a Horizontal Extended Reach Well, Enabling Improved Reservoir Management
Authors: Wills Andrew , Wheatley Jason , Sau Rajes , Jimenez Jose , Ulloa Joel 
Published: March 2019

Abstract
The latest developments in well construction rely on advanced drilling and completion technologies to withstand increased wellbore deviation, tortuosity, and complex geometry challenges necessary to access reservoirs, which can create challenges to cement placement between reservoir zones. Hence, well integrity and reservoir management concerns can arise given the possibility for multiple reservoirs to communicate, resulting in undesired crossflow and water production because of poor cement isolation.
Poor cement placement behind casings, ineffective zonal isolation, and well integrity issues have been traditionally addressed using workover or drilling rigs to remove production tubing and perform either a remedial cement squeeze or zonal abandonment for subsequent sidetrack. However, this generally entails production deferral, capital-intensive rig rates, the potential risks of pulling and running production tubing, which often translates in formation damage from killing the well, large wellsite footprint requirements, and higher logistic demands for rig support equipment.
This paper describes the systematic process used to identify, diagnose, design, and execute a successful inter-reservoir crossflow mitigation operation in a naturally fractured carbonate formation in Abu Dhabi using a cost-effective solution with rigless coiled tubing-deployed technologies and a hydrocarbon-based microfine cement slurry that activates upon contact with water. The results enabled the operator to restore reservoir integrity, improve reservoir management, and enhance water sweep.
Post-operation reservoir evaluation validated the successful use of the technology for rigless zonal isolation using coiled tubing (CT) for the first time in the United Arab Emirates, providing significant cost benefits and new best practices to reduce the water cut and restore wellbore integrity.
When Petrophysics Meets Big Data: What can Machine Do?
Authors: Xu Chicheng , Misra Siddharth , Srinivasan Poorna , Ma Shouxiang 
Published: March 2019

Abstract
Petrophysics is a pivotal discipline that bridges engineering and geosciences for reservoir characterization and development. New sensor technologies have enabled real-time streaming of large-volume, multi-scale, and high-dimensional petrophysical data into our databases. Petrophysical data types are extremely diverse, and include numeric curves, arrays, waveforms, images, maps, 3-D volumes, and texts. All data can be indexed with depth (continuous or discrete) or time. Petrophysical data exhibits all the "7V" characteristics of big data, i.e., volume, velocity, variety, variability, veracity, visualization, and value. This paper will give an overview of both theories and applications of machine learning methods as applicable to petrophysical big data analysis.
Recent publications indicate that petrophysical data-driven analytics (PDDA) has been emerging as an active sub-discipline of petrophysics. Field examples from the petrophysics literature will be used to illustrate the advantages of machine learning in the following technical areas: (1) Geological facies classification or petrophysical rock typing; (2) Seismic rock properties or rock physics modeling; (3) Petrophysical/geochemical/geomechanical properties prediction; (3) Fast physical modeling of logging tools; (4) Well and reservoir surveillance; (6) Automated data quality control; (7) Pseudo data generation; and (8) Logging or coring operation guidance.
The paper will also review the major challenges that need to be overcome before the potentially game-changing value of machine learning for petrophysics discipline can be realized. First, a robust theoretical foundation to support the application of machine leaning to petrophysical interpretation should be established; second, the utility of existing machine learning algorithms must be evaluated and tested in different petrophysical tasks with different data scenarios; third, procedures to control the quality of data used in machine leaning algorithms need to be implemented and the associated uncertainties need to be appropriately addressed. The paper will outlook the future opportunities of enabling advanced data analytics to solve challenging oilfield problems in the era of the 4th industrial revolution (IR4.0).
Applications of Artificial Neural Networks in the Petroleum Industry: A Review
Authors: Alkinani Husam H. , Al-Hameedi Abo Taleb , Dunn-Norman Shari , Flori Ralph E. , Alsaba Mortadha T. , Amer Ahmed S. 
Published: March 2019

Abstract
Oil/gas exploration, drilling, production, and reservoir management are challenging these days since most oil and gas conventional sources are already discovered and have been producing for many years. That is why petroleum engineers are trying to use advanced tools such as artificial neural networks (ANNs) to help to make the decision to reduce non-productive time and cost.
A good number of papers about the applications of ANNs in the petroleum literature were reviewed and summarized in tables. The applications were classified into four groups; applications of ANNs in explorations, drilling, production, and reservoir engineering. A good number of applications in the literature of petroleum engineering were tabulated. Also, a formalized methodology to apply the ANNs for any petroleum application was presented and accomplished by a flowchart that can serve as a practical reference to apply the ANNs for any petroleum application. The method was broken down into steps that can be followed easily. The availability of huge data sets in the petroleum industry gives the opportunity to use these data to make better decisions and predict future outcomes. This paper will provide a review of applications of ANNs in petroleum engineering as well as a clear methodology on how to apply the ANNs for any petroleum application.
Automated Artificial Intelligent Pressure Gradient Analysis for Fluid Contact and Compartmentalization Analysis
Authors: Stark Daniel , Jones Christopher , Dai Bin , van Zuilekom Anthony 
Published: March 2019

Abstract
The reservoir compartmentalization structure and fluid contacts of a field are essential for determining the value of a reservoir asset and provide the two primary purposes of pressure gradient determination. Several new straightforward data-analytical methods have been developed to extract pressure gradient information based on physical properties of the reservoir and meta-analysis of derived pressure gradient information. These methods can be used to provide near real-time feedback about the pressure measurements quality.
This paper describes two distinct methods to determine reservoir compartmentalization structure and fluid contacts. The first method implements statistical evolution to rapidly identify pressure gradients. The second method transforms identified pressure measurements into a meta-analytical visual representation of pressure gradients vs. depth with additional input from measurement consistency. Both methods rely on the accurate removal of pressure outlier data, such as that attributable to supercharging. A new technique using expert knowledge of physical constraints was implemented for reliable outlier removal. The two methods then diverge in subsequent conditioning of the data, but re-converge in adapting an efficient fitting method to extract the desired information.
Both methods provide reliable removal of pressure data that are not related to formation fluid densities, regardless of reservoir number, fluid number, or fluid type. To date, the removal procedure removes more than 95% of outliers and retains more than 90% of accurate pressure data. Both methods also return the correct number and types of fluids. Although pressure gradient estimation can vary by up to 50% for fluid zones of less than 50 ft, the estimation error of the pressure gradients is reduced to less than 3% for fluid zones greater than 100 ft. Furthermore, fluid breaks can be calculated to within 8 ft for the statistical evolution method and to within 30 ft using the visual method. Finally, although the statistical evolution method is markedly faster than the visual method, both techniques provide feedback within a few minutes.
The methods discussed provide feedback about the necessity to retake or take more pressure data during formation-pressure surveys within minutes. This feedback eliminates the delay in reservoir property estimation and greatly increases the reliability and quality of pressure data obtained. The methods presented also use a new application of data meta-analysis to reduce processing time and increase reliability.
A New Decline Curve Analysis Method for Layered Reservoirs
Authors: Jongkittinarukorn Kittiphong , Last Nick , Escobar Freddy , Maneeintr Kreangkrai 
Published: March 2019

Abstract
This study presents a new method to improve production forecasts and reserves estimation for a multilayer well in the early stages of production, using Arps’ hyperbolic decline method to model the decline rate of each layer. The method can be applied to both oil and gas wells.
The new approach generates the profiles of instantaneous decline rate (D) and instantaneous decline exponent (b) from the historical flow rate (q). Because of the inherent noise in the production data, a regression technique is applied to smooth the flow rate data and the analysis is performed on the smoothed data. History matching is performed not only on the profile of q, but also on the profiles of D and b. The results are the unique decline parameters (qi, Di, and b) for each layer.
For a multi-layer well, the values of D and b vary with time, which means that its performance cannot be modeled using a conventional single-layer well approach. Furthermore, the well-known non-uniqueness problem from history matching is magnified in a multilayer well: many models can successfully match the production profile in the short term but fail to match it in the longer term. Only the correct model can match the profiles of q, D, and b over both the short-term and the long-term. The proposed method provides the correct unique decline parameters (qi, Di, and b) for each layer, during the early stage of production, and these parameters are then valid for the life of the well. The method works well for both synthetic examples and actual field data.
The novelty of the new methodology is the ability to provide the decline parameters for each layer at an early stage of production, which can then be used for production forecasting in the long term. The non-uniqueness problem from history matching is solved.