bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multifunctional High Temperature Water-Based Fluid System
Authors: Panamarathupalayam Balakrishnan , Manzoleloua Cedric , Sebelin Linus , Aung Tint Htoo 
Published: March 2019

Abstract
The development of deep oil and gas reservoirs requires high temperature stable drilling fluid systems. The properties of conventional polymers in water-based systems decline above 300°F which led to the development of the new high temperature water-based system.
The high temperature water-based system, featuring a newly developed synthetic polymer, has been developed to provide enhanced rheological profiles and fluid loss control, along with long-term stability under elevated temperature and pressure conditions. The system has been designed to minimize formation damage by forming a thin and ultra-low permeable filter cake. The versatility of the developed polymer allows the new system to be formulated at a wide range of densities using most conventional oilfield brines including monovalent and divalent halide and formate brines.
The clay-free high temperature drilling fluid has stable rheological properties, no gelation and low sag tendencies which are ideal for high temperature logging applications. Also, the highly branched nature of the polymer provides a rheological profile suitable for coil tubing applications.
A new breaker package was developed along with the high temperature water-based system to slowly and uniformly clean-up its deposited filter cake, reducing near wellbore damage and maximizing production when the system is used to drill open-hole completion wells.
This paper summarizes the fluid design in the lab and recent field applications, where the new high temperature polymer-based system was successfully deployed in different locations around the world.
High-Order Accurate Method for Solving the Anisotropic Eikonal Equation
Authors: Waheed Umair bin 
Published: March 2019

Abstract
High frequency asymptotic methods, based on solving the eikonal equation, are widely used in many seismic applications including Kirchhoff migration and traveltime tomography. Finite difference methods to solve the eikonal equation are computationally more efficient and attractive than ray tracing. But, finite difference solution of the eikonal equation for a point source suffers from inaccuracies due to singularity at the source location. Since the curvature of wavefront is large in the source neighborhood, the truncation error of the finite difference approximation is also significant, leading to inaccuracies in the solution. Compared to several proposed approaches to tackle source singularity, factorization of the unknown traveltime is computationally efficient and simpler to implement. Recently, a factorization algorithm has been proposed to obtain clean first order accuracy for tilted transversely isotropic (TTI) media. However, high order accuracy of traveltimes is needed for quantities that require computation of traveltime derivatives, such as take off angle and amplitude. I propose an iterative fast sweeping algorithm to obtain high order accuracy using factorization followed by Weighted Essentially Non-oscillatory (WENO) approximation of the derivatives. Although this method yields highly accurate traveltimes but it also results in increased computational load. Therefore, I propose a parallel fast sweeping algorithm to compute fast and accurate solution of the anisotropic eikonal equation. High accuracy is achieved first by using factorization followed by the WENO approximation of derivatives, whereas computational speed up is obtained by sweeping the computational domain in parallel. With a large number of CPUs, significant reduction in computational cost can be achieved for large 3D models. Numerical test shows improvements in accuracy of the TTI eikonal solution.
Advanced Wellbore Stability Analysis for Drilling Naturally Fractured Rocks
Authors: Han Yanhui , Liu Chao , Phan Dung , AlRuwaili Khalid , Abousleiman Younane 
Published: March 2019

Abstract
An advanced wellbore stability analysis software product has been developed in-house at Aramco. This product offers three analysis modules: (1) the classical mechanical module (elastic); (2) the time-dependent analysis module (poroelasticity); and (3) the time-dependent analysis of naturally fractured rock module (dual-porosity and dual permeability poroelasticity). The stress and pressure analyses are integrated with four rock failure criteria (Mohr-Coulomb, Drucker-Prager, Modified Lade, and Hoek-Brown) to calculate critical mud densities. The basic mechanical module is similar to the wellbore stability module provided in the most-frequently-used drilling geomechanics software. What sets this product apart from the others is that no commercial drilling software to date has the time-dependent stress and pressure analyses modeled by this product's poroelastic and dual-porosity poroelastic modules, which can capture real-time phenomena introduced by the time-dependent fluid pore pressure perturbation and the wellbore time-dependent failures in tension and/or compression.
Using Hypothesis Testing to Evaluate Key Performance Indicators in Real Time: An Edge Computing Use Case
Authors: Kowalchuk Peter 
Published: March 2019

Abstract
Harvesting vast amounts of data has long been identified as an enabler of operational performance. The measurement of key performance indicators is a routine practice in well construction, but a systematic way of statistically analyzing performance against a large data bank of offset wells is not a common practice. The performance of statistical analysis in real time is even more rare. With the introduction of edge computing, devices capable of complex analytical functions in physical proximity to sensors and operations, this practice can be realized. Two case studies are presented: rate of penetration (ROP) and amount of vibration per run.
Hypothesis testing is a statistical method in which a sampled dataset is compared against an idealized or status quo model. This model is built using many samples from a population. The characteristics of the population are then inferred from these samples. The model is built in centers where large amounts of data are available. These models are then transferred to an edge device in the field. The device collects real-time data and compares results to the status quo model. In the two cases presented, hypothesis testing was used to determine maximum and minimum levels of ROP and downhole vibration. This information is used to determine the effectiveness of new drilling practices, technologies, or methodologies. Because calculations are performed in real time, changes to drilling practices can be adopted quickly.
The ROP case was performed at a US operating unit; the vibration case was performed in a Middle East unit. The models showed what improvement values should be. It was revealing to find wells that were thought to be poor performers were actually well within the population normal. Wells were also found that were thought to be good performers, but where new drilling methods were used, actually fell within the population model and thus suggested that the new methods had not affected performance. By performing this analysis on the edge device, operations can make changes early in such a way that results fall outside the status quo model and deliver real performance improvements.
The paper presents the novel use of statistical models calculated in data centers in conjunction with real-time operations. Similar approaches in technical and physics modeling exist in which models are produced in the office and used in the field. However, building models for operations management, from a large bank of offset data, and performing analysis in the field with real-time data is a not common practice. This paper shows both technology and statistical methods that provide a valid scientific framework for operational performance improvement.
Turning an Offshore Analog Field into Digital Using Artificial Intelligence
Authors: Espinoza Roberto , Thatcher Jimmy , Eldred Morgan 
Published: March 2019

Abstract
Replacing all analogue sensors in the oil field is very costly and normally only a fraction of them is done. Currently, there is no cost-effective method to efficiently, reliably and accurately capture analogue meter readings in a digital format. Operators are then left with only two options: either replace them with digital (high capex) or continue with manual gathering (high opex). This paper shows how computer vision and artificial intelligence was used for the first time to capture analogue field gauges data with dramatic reduction of cost and increase reliability.
This unique solution was implemented in the Cheleken Oil field, Caspian Sea, Turkmenistan. In the offshore platforms, only low-cost cameras were necessary, and gauges were identified using QR codes. During the field trial, operators were only required to take pictures of the gauges at a given interval of time and upload the photos to the application. After an innovative process of calibration, the acquired images were processed using artificial intelligence and deep learning computer vision.
Routine manually gathered data was compared with data collected using this solution with the following observations made: Date/time: Operators usually round time. The solution described records time on the captured pictures automatically.Value: Manually gathered data is subject to reading, typing and transcription errors. This solution has no error (provided a good calibration is done).Data Modification: Data gathered automatically with this solution has no human intervention. Therefore, is not subject to alteration, copying or duplication.Data collection with pictures was completed in 1/10th of the time that manual processes take.The business benefits from quicker operator rounds with improved accuracy in meter reading data, and time stamps. The administrative burden for operators of filling in extensive spreadsheets which are prone to error was reduced, this allowed them to collect more meter readings or be reassigned by management to more important scopes of work that bring greater value to the business. Once more it was proved that "a picture is worth a thousand words ".
This solution offers an excellent opportunity for digitizing the marginal section of the field and provides a unique way to turn all analogue data into digital with a very low cost of implementation, on an infinitely scalable platform that is vendor agnostic and simple to manage.
Integrated Formation Evaluation Using High Resolution Sedimentary and Facies Analysis an Aid for Field Development: A Case Study from North Kuwait
Authors: Sanyal Arunava , Kumar Sanjeev , Al Awadh Ahmed , Al Samhan Sarah , Al Azmi Jassim , Sikdar Koushik , Sultan Gamal Ali , Das Sourav 
Published: March 2019

Abstract
Zubair Formation is one of the key producers in North Kuwait; however, the reservoir complexity and hydrocarbon movement along with pressure depletion always poses challenge for determining the perforation and completion strategy to optimize the production. Zubair Formation is broadly divided into three parts e.g. upper, middle and lower, the upper and lower units are of utmost importance for the current study. An integrated approach was adopted utilizing the high-resolution borehole image outputs; which has not only helped in identifying thin bedded reservoir zones but also facilitated the understanding of detail reservoir geology and sand dispersion.
Integrated formation evaluation and workover design is always the key to sustain the production and it becomes even more important when the reservoir is highly heterogeneous in nature and coupled with declining pressure trend. Therefore, an innovative methodology was necessary to address the uncertainties. High resolution borehole images were utilized to determine the sand count, which can detect even the thinnest reservoir layer in the formation. Heterogeneity analysis was also performed to understand the relative sorting of the different reservoir units; sorting has a direct relation with reservoir permeability and thus reservoir productivity. High resolution sedimentary analysis was performed to understand the detailed sedimentology using the borehole image derived dip data; cross bedding types were identified which provides fair idea about depositional energy condition along with depositional environment. All the high-resolution inputs were integrated with openhole logs and volumetric results, which led to a clear deterministic picture of the reservoir, based on which crucial decision was taken.
This integrated approach was adopted in three deviated well sections in Zubair formation, which has facilitated in improving the well performance. Detail sedimentary analysis and cross bedding typing in multiwell helps in fine tuning the sand dispersion in the reservoir model; which in turn found to be helpful for deciding future well locations.
Using Unstructured Grids for Modeling Complex Discrete Fracture Network in Unconventional Reservoir Simulation
Authors: Ding XiangYang 
Published: March 2019

Abstract
Unstructured gridding has become an important subject matter in reservoir simulation. Its flexibility of grid generation and enhanced simulation accuracy have gained popularity in reservoir simulation, especially when modeling reservoir with complex wells and faults. In this work, unstructured gridding is being extended to model the complex discrete fracture network in unconventional reservoir simulation. The typical way of gridding in reservoir simulation is using structured grid due to the easiness of cell indexing but the drawback of zig-zag approximation of reservoir geometry is also apparent on the cells near well, fault or fracture. However, such challenge is addressed when using unstructured grid, where the grid cells can be generated conforming to the geometry without large extent of approximation. In this work, 2.5D unstructured PEBI gridding is being used to model the complex discrete fracture network where the fracture geometry can be straight line or irregular. Grid density is controlled by a multi-level scheme based on region of interest in the reservoir and geometry locations of well and fracture. Near-well and near-fracture flow modeling are being enhanced with the use of high resolution grids in the area close to wellbore and fracture pathway. Particularly in the near-fracture area, the unstructured gridding method generates Logarithmically Spaced Locally Refined (LSLR) grid to capture the transient in the ultralow-permeability shale, to satisfy the requirement to model the large fracture pressure gradient which is sensitive to stress changes.
This adaption of unstructured gridding method in modeling fracture in unconventional reservoir brings the gridding flexibility to model the complex fracture geometry. By using the fracture oriented grid density control scheme, pressure gradient change in near-fracture area can be modeled with enhanced accuracy. Benefits of using unstructured grid are demonstrated on simulation example by using unstructured grid and being compared with the structured grid.
This presented work introduces an enhanced way of complex fracture modeling in unconventional reservoir simulation by using unstructured gridding framework. It improves the grid generation efficiency and simulation accuracy, which is valuable in unconventional reservoir simulation and development.
Enhanced Augmented/Mixed Reality and Process Safety Applications
Authors: Potts Jeff , Sookdeo Terrance , Westerheide John , Sharber Dustin 
Published: March 2019

Abstract
As the oil and gas industry undergoes a digital transformation, the massive volume and variety of information being ingested at increasing velocity necessitates new methods of data interaction for decision making. Additionally, effective management of safety risks and flawless operational execution in an evolving oil and gas industry requires innovative applications of digital technology. By superimposing contextually-relevant digital information on the physical world, augmented and mixed reality (AR/MR) technologies have tremendous potential to meet these challenges by providing a more intuitive way to interact with data, train personnel, and ensure process safety.
However, a major challenge with AR and MR technologies is the limited processing power and capability of available hardware. A cloud-based software platform has been developed to overcome computational limitations of AR and MR devices, enabling interaction with significantly more complex 3D content. Additionally, this enhanced AR/MR software platform enables real-time connectivity across different hardware architectures – such as smartphones and Microsoft HoloLens devices – creating powerful new capability for remote collaboration. This unique software platform transforms consumer-grade AR and MR devices into powerful industrial tools useful for a variety of oil and gas applications.
This study will illustrate the functionality enhancements provided by this software platform and how it greatly increases the application potential of AR and MR, including a case study on adoption of this enhanced AR/MR technology for process safety using threat response drill (TRD) scenarios. Enhanced AR and MR provides full-scale virtual TRD scenarios that enable practical demonstration of operational readiness and proactive risk management. Crew response capability and human performance can be collaboratively evaluated with gamified AR/MR techniques, allowing for multiple outcomes based on user inputs through multiple interaction modalities, enabled by the underlying software platform. Enhanced AR/MR enabled by this software platform can drive major improvements in process safety and ultimately help reduce CAPEX, increase efficiency, and mitigate risk across the oil and gas industry.
Integrated NMR Fluid Characterization Guides Stimulation in Tight Sand Reservoirs
Authors: Ighodalo Endurance , Hursan Gabor , McCrossan John , Belowi Ali 
Published: March 2019

Abstract
Unconventional tight reservoir sands have low porosity and very low permeability (mostly less than 0.1mD) due to their fine grain size and poor grain sorting that is often exacerbated by extensive diagenetic effects such as cementation and compaction. Petrophysical evaluation in these formations is very challenging. Conventional downhole logs such as density, neutron, sonic, gamma ray and resistivity measurements provide limited information on pore size variations and often missed Key geological features especially at the early stages of reservoir development. Fluid characterization at the earliest possible stage is paramount to guide the development of these reservoirs where tight well spacing, stimulation (fracturing) and or horizontal well completion is usually required. The main objective of this paper is to show a process of fluid characterization in unconventional tight sand that guides reservoir stimulation.
Porosity partitioning using nuclear magnetic resonance (NMR) logging data helps address these challenges in three distinct steps. First, the 1-dimensional (1D) NMR T2 spectrum quantifies the amount of bound and free fluids pore space and reveals reservoir quality with unique sensitivity. In this step, the NMR fluid substitution method was utilized to ensure consistency between NMR logs in oil-based mud (OBM) and water-based mud (WBM) systems. Second, the free fluids are further subdivided into hydrocarbon and water phases using a 2-dimensional (2D) NMR T1/T2 processing technique. Third, the hydrocarbon phase is subdivided again into liquid and gas phases where a gas flag is turned on whenever the NMR gas signal significantly exceeds measurement uncertainty. This enables detection of live hydrocarbons with high gas-oil ratio (GOR).
This paper presents the integration of NMR analysis into petrophysical evaluation of an unconventional tight sand reservoir. The evaluation helped optimize the best interval for stimulation. Fluid sample acquired with formation tester correlated very well with NMR log-based fluid prediction.
Integrated NMR analysis, including bound fluid vs. free fluid analysis and 2D NMR-based fluid characterization, including gas indicator flag, was applied to establish the presence and type of hydrocarbon in tight sands and select the best representative interval for stimulation. The continuous reservoir quality and fluid distribution profiles provided by these logs were beneficial for the geological understanding and complex formation testing operations in this challenging reservoir.
Virtual Workstation Deployment in Malaysia Oil and Gas Company: Performance Improvement and Cost Reduction Experience
Authors: Mat Dait M Hafiz 
Published: March 2019

ABSTRACT
The objective of the paper is to share the experience and result of deployment of Virtual Workstation in Malaysia Oil and Gas Company replacing the more expensive high-end workstation. This is a part of company's digital transformation program towards the 4th Industrial Revolution. VWS is a modern technology that accelerates and improves subsurface and petroleum engineering application and function. It replaces outdated high-end workstation set-up. In high-end workstation set-up, subsurface technical software was installed at user workstations. Master Data on the other hand, located at centralized data center, BDC; but in order for the user to retrieve the data, it has to go through regional data center at KPC first. All these processes happened through existing small 1 GB cable networks capacity. Separate software and data location, multiple location points for data retrieval and weaker cable network capacity lead to less efficient software performance and data insecurity. But in VWS set-up, issues of under-performed software and data security are eliminated. Now both software and data are installed and located at BDC. Then the user will access their software and data virtually via company's intranet at with the strength of 10 GB cable network capacity that VWS has. VWS deployment resulting in: i) Performance and productivity: increased efficiency for technical applications and optimization of technical resources. ii) Cost: optimization of cost on IT infrastructure. iii) HSE: Reduced IT footprint and energy consumption. iv) Data security: increased data security. v) Flexibility: improved collaboration for technical users. vi) Standardization: standardized desktop environment for enhanced support. VWS deployment only need the VWS system and standard normal workstation to function as good as the more expensive high-end workstation. With VWS, standard workstation is enough to process and run petroleum engineering software and data, since the workstation only act as a visualizer of their actual software and data that located in BDC. With deployment of standard workstation instead of high-end workstation, VWS expected to contribute to cost saving of RM 86k per user for 3 years of leasing.