bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advances in Parallel Reservoir Simulation Technology, Using Multi-Threaded Algorithms
Authors: Mohajeri Sina , Eslahi Reza , Bakhtiari Maryam , Zeinali Mostafa , Rajabi Hamed , Alizadeh Ali , Sharifi Ebrahim , Mortezazadeh Emad 
Published: November 2018

Abstract
The popularity of parallel reservoir simulation has increased in recent years due to availability of multi-core CPUs and the opportunity for run-time reduction, especially in complex and fractured reservoir models that include large amounts of data. However, the accuracy of classical domain decomposition techniques significantly decreases as the number of processing units increases. The scope of this work is mainly concentrated on development of multi-threaded algorithms to overcome the mentioned problem in parallel reservoir simulations. In this work, at first, a newly developed, parallel, three dimensional, fully implicit, three-phase black-oil reservoir simulator is introduced. For solving large scale linear systems produced in giant black-oil models, which are probable cases in real world reservoir models, BiCG-Stabilized linear solver, enhanced with various preconditioners including, Blocked Incomplete LU factorization, Constrained Pressure Residual using Algebraic Multi-Grid as its pressure smoother is constructed with a variety of parallelization techniques applied in each part. The presented multi-threaded algorithms can utilize any user-defined number of CPU cores. The algorithm has been evaluated by SPE10 with 1122000 grid blocks and a real data file containing 277875 grid blocks. The result indicates that increasing the number of CPU threads does not have any negative effect on the simulation performance in case of high memory bandwidth limits. For SPE10 data file, 1.70, 2.4, and 2.3 speedup ratios (in comparison with a single thread) has been observed for 2, 4, and 6 parallel threads, respectively. In the real case, the simulation speed is increased by a factor of 1.49, 1.74, and 1.75 for 2, 4, and 6 parallel threads, respectively. Using multi-threaded algorithms as a novel approach in parallel simulations, the solution configuration does not change from the single core case and follows the same exact path. This however is not the case for other simulators that use domain-decomposition techniques. These techniques insert numerical errors in the solution of linear systems, which lead to convergence problems in the whole system.
The Value of Integrated Borehole Image Analysis to Refine Geological Models: An Example From the Greater Burgan Field, Kuwait
Authors: Al-Enezi Bashar , Kostic Boris , Foote Nicolas , Filak Jean Michel , Al-Mahmeed Fatimah , Al-Shammari Obaid , Bertouche Meriem 
Published: November 2018

Abstract
Resistivity image logs are high-resolution tools that can help to unravel the depositional and structural organisation in a wellbore. They provide a particularly powerful dataset when calibrated against core, maximising their benefit for reservoir characterisation. This paper shows examples how very detailed image assessment from selected wells in the Greater Burgan Field has helped to constrain the stratigraphic model and depositional interpretations of the Cretaceous Burgan and Wara reservoirs.
A multidisciplinary study of 123 cored wells, integrating core sedimentology, petrography, bio- and chemostratigraphy, wireline well and resistivity image logs, has delivered a robust stratigraphic and depositional framework for one of the most important reservoirs in the world's largest siliciclastic oil field. A descriptive image facies scheme that has been calibrated against core and conventional well logs captures the lithological variation, sedimentary features and surfaces of the reservoir, providing a detailed proxy for the sedimentological evaluation of uncored intervals and wells.
The sand-rich lower Burgan (4S) comprises fine to very coarse-grained fluvial channel sandbodies that are locally separated by laterally restricted mudrock baffles. Image and core analyses suggest that the majority of the sandstones are high-angle cross-stratified and form stacked barforms within amalgamated channel sandbodies. Their consistent orientation towards the NE-E supports a low-sinuosity (braided) fluvial system resulting in a relatively simple, sheet-like depositional architecture across the field. Although slightly finer grained, the cored middle Burgan channel sandbodies (3SM) are similar to those in the lower Burgan. However, palaeoflow data from the imaged wells show a higher directional spread in the order of c.60-90° with a dominantly N to E orientation of the sandy barforms. Careful analysis of the orientation of the bounding surfaces between the sandstone packages indicates nearly equal proportions of obliquely and roughly parallel dip orientations in some wells. This suggests the formation of at least some lateral (point) bars and possibly the presence of higher sinuosity channels implying that sandbody architecture and fluid flow pathways could be more complex in the middle Burgan relative to the lower Burgan.
The examples from the Burgan and Wara Formations highlight the value of integrated image analysis for reservoir characterisation by delivering a consistent descriptive framework, embedding different datasets.
Basrah NGL: Best Practices for a New Sour Gas Processing Hub in Southern Iraq
Authors: Nour Tamir Abo , Bodewes Theo , Wharton Mark , Verlaan Cor 
Published: November 2018

Overview
The objectives of the paper are to use the Basrah NGL gas processing project in the Basrah Gas Company JV (BGC) to demonstrate best practice application of industry solutions and appropriate technology selection, aligning with project value drivers whilst managing technical and non-technical uncertainties in decision making.
In mid-2018 contracts were awarded for the Basrah NGL gas processing hub in Southern Iraq that will set the competitive cost and schedule benchmark for new gas plants in Iraq. Embracing Shell and industry experience to deliver a standardized and replicable design was a key priority for the project team and JV partners. Technology selections were evaluated against project value drivers to support robust decision making for current and future operations, and contracting strategy selected considering synergies across the portfolio through bundling and building on in-country experience.
Two trains of 200 mmscf/d each have been awarded in the first development phase, however future expansion requirements are much simplified with the facility designed to be expandable to 5 replicated trains providing a total 1000 mmscf/d capacity in line with the upstream gas production forecast. The benefits of standardisation and replication lock in further cost and schedule savings for subsequent gas processing trains and continue to lower unit development and operating costs. In line with the future plans for the facilities, pre-investments were made for major infrastructure investments including gas and LPG export pipelines and high voltage power supply.
The BGC NGL processing train design is flexible to the range of gas qualities prevalent in Southern Iraq. Technology selections have been appropriately made to consider current and future requirements both in terms of ethane and LPG recovery but also acid gas removal and Sulphur recovery solutions. In the case of Sulphur recovery, a Shell and-Paques developed, Thiopaq technology is selected to provide the most capital efficient flexible solution, whilst also providing ease of scale-up to higher recovery rates as the upstream gas supply becomes progressively more sour (with higher H2S content) over time.
DCCD™ - A New Dual Column Cryogenic Distillation Technology for Natural Gas Sweetening: The Operations of a Laboratory Scale Pilot Plant
Authors: Picutti Barbara , Franzoni Guido , Vergani Paolo , Brignoli Fabio , Del Gesso Lucrezia , Rabino Francesca 
Published: November 2018

Abstract
This work presents the highlights of the results obtained from the operations of a laboratory-scale pilot plant, designed for the demonstration of an innovative gas sweetening technology. The theory behind the process, based on a dual-pressure cryogenic distillation, will be described and checked against the experimental results from the plant.
Experimental test runs with different feed gas compositions have been carried out: mixtures with a variable content of CH4, CO2, C2 and C3 have been tested. The design of the distillation columns of the laboratory-scale experimental plant allowed to process feed gas with a CO2 content up to 50 mol%, while C2 and C3 content has been limited to few percentages, aiming to reproduce the situation of a lean gas composition. Data from the plant have been used to cross-check predictions of commercial process simulators (e.g. Aspen HYSYS® V10).
The experimental results obtained from the laboratory-scale pilot plant allowed to successfully demonstrate the theoretical concept underlying the new dual-pressure cryogenic distillation technology. Adjusting the operating conditions of the pilot plant has allowed to treat gas mixtures with different contents of CH4, CO2, C2 and C3, and to study the effect of the operational parameters on the system. The presence of heavier hydrocarbons proved to be beneficial in avoiding solid CO2 formation, in accordance with available literature. The comparison between experimental data and predictions by commercial process simulators allowed to gather more information on the relevant thermodynamic framework, improving the overall degree of confidence in the models to be used during the design phase.
The increasing natural gas demand challenges the industry to find new solutions for the profitable exploitation of natural gas fields with a higher than ever CO2 and H2S content. In this scenario, cryogenic distillation represents a cost-effective alternative to traditional sweetening technologies. The concept of the new technology has been demonstrated through the operations of a laboratory scale pilot plant, confirming its capability to produce sweet gas while avoiding CO2 solidification.
Integrating Geomechanical Modeling and Production Data for Decision Support in Deep Gas Reservoirs in Oman
Authors: Dobroskok Anastasia , Al Zadjali Ruqaiya 
Published: November 2018

Abstract
Geomechanical modeling of hydraulic fracturing in deep gas reservoirs in Oman is complicated by high uncertainties in key parameters. This study aims to adopt a physics-based data analytics technique to model geomechanical behavior of rocks. The paper also presents the methodology of linking geomechanics with well performance. Finally, the integration of the results into a decision support system is discussed.
The majority of deep gas reservoirs in Oman are tight. The permeabilities are in the sub-millidarcy range. Hydraulic fracturing helps to unlock the reserves. Meanwhile, proper hydrofracture design is required to optimize the development of these complex reservoirs. Due to high stresses, unclear processes governing hydrofracture propagation, and complex depositional and diagenetic histories, the applicability of standard hydrofracture modeling techniques becomes questionable. Proper surveillance design and in-depth analysis of the monitoring data assist in testing the range of applicability of the modeling tools. The analysis also aids in characterizing the influence of the processes not captured within the models.
Recently the development of deep gas reservoirs in Oman started to benefit from horizontal well technology. Similarly to other horizontal developments, the question of proper well architechture and stimulation design was raised. In this study, the data pertaining to historical vertical wells was collated to understand the processes governing hydrofracture placement. The data indicated the presence of strong fracture barriers and of highly stressed zones which affect the ability to create sufficient fracture conductivity. Further, geomechanical models were calibrated to allow for realistic estimate of the contact area between the fracture and reservoir. Analysis of the production data indicated that productivity was often limited by the factors not captured in the models (e.g., suboptimal cleanup). For proper planning, risk factors may be chosen to reflect the loss of productivity. In the next step, the learnings from the vertical wells served for characterizing hydrofracturing in horizontals. Analysis of the data indicated that due to near-wellbore complexity and choking effect the productivity of an individual fracture in a horizontal well was only a fraction of that in a vertical well. As a final step all the data along with their interpretation are being incorporated into the library of hydrofracture scenarios. Future development will rely on searching for the analogs and selecting a design fitting all applicable scenarios. The paper presents an overview of the surveillance data analysis. The results of the analysis allow for creating a library of the development scenarios, which serve as a basis for a decision support system aimed at streamlining hydrofracture and well planning design.
New Approach to Fluid Typing Concepts in Tight Carbonate Source Rocks
Authors: Steiner Stefan , Mosse Laurent , Raina Ishan 
Published: November 2018

Abstract
Assessment of the porosity - fluid system, while challenging, is important in source rock oil plays. This is due to the wide range of hydrocarbon weight fractions, from bitumen to light hydrocarbon encountered in the source rock, along with the presence of both, the organic and the inorganic porosity systems, simultaneously. In such a play, while comparing zones of similar total porosity and water saturation, intervals with a better fluid type and porosity system will contribute more to the flow than other zones. In this paper an approach to poro-fluid typing a source rock is presented through examples from a carbonate source rock case study from the Middle East.
The following core measurements were acquired on two wells: 1. NMR T1-T2 measurements on as received, oil saturated and water saturated samples, 2. Retort measurements for effective and total porosity and saturation analysis 3. Solvent extraction saturations for quantifying total hydrocarbon saturation, and 4. Mercury Injection Capillary Pressure Analysis for estimating pore throat size distribution. TOC measurements were also acquired on all the samples. A classification technique called the Blind Source Separation analysis (BSS) is carried out on the combined dataset of NMR 2D maps and various classes are identified based on the typical signatures observed on the maps in different saturation states.
The classes identified using BSS were correlated to other core measurements to assign a physical meaning to each class. Based on the results, three key poro-fluid groups are identified. These groups are bitumen hosted porosity, porosity in the organics, and inorganic hosted porosity. By integrating results from MICP and SEM, we identify the typical pore sizes observed in the above groups and recommend zones that will bet better contributors to flow. Finally, we tie the results back to the limited measurements available in the log domain to predict zones with better flow potential.
Reactive Liner Perforating Technology used to Improve Efficiency of Hydraulic Fracturing Operations
Authors: Nunez Alvaro Javier , Molenaar Mathieu , Al-Salmi Masoud , Al-Farei Ibrahim , Gheilani Hamdan , Sayapov Ernest , Al-Shanfari Abdul Aziz 
Published: November 2018

Abstract
Deep exploration and gas wells with very tight formations to be hydraulically fractured in the Sultanate of Oman, have been preferably perforated with Abrasive Jet perforating systems in order to reduce the perforating skin and to be able to break down the formation compared to the regular deep penetration shaped charges which historically have been unsuccessful used. The complexity of the Abrasive Jet perforating operations requires Coil Tubing, Sand Management System (SMS), specialized perforator BHA, correlating devices, pumping and mixing equipment and a substantial quantity of fluids and sand per interval.
Perforating guns with reactive liner technology, conveyed with electric line, have been considered for these types of wells. This technology delivers enhanced perforations facilitating fracturing operations by reducing the break down pressures. Initially well data from three exploration wells "A", "B" and "C" were extensively evaluated with very high chances to succeed. The job execution was planned parallel to the Abrasive Jet perforation in case the formation would have not broken down after the gun perforations. In well "A" two stages were executed successfully using the reactive liner shape charge technology while in the well "B" the first stage was neither broke down after reactive liner charges nor after Abrasive Jet perforations; the second stage in well "B" was successfully executed after the reactive shape charge gun perforations. This initial success of these two exploration wells was replicated in another gas field also with tight formations which historically has been perforated with Abrasive Jetting near well "C".
As a result of this, the efficiency, the perforating accuracy and the cost savings are substantial improved; the HSE exposure is much less due to the fact that less resources are needed compared to the requirements for Abrasive Jet. This paper will go thru the design, planning, execution, results and the big step change in the fracturing operations in these types of wells in which Abrasive Jetting is not always the best preferred option.
Big Data-Driven Advanced Analytics: Application of Convolutional and Deep Neural Networks for GPU Based Seismic Interpretations
Authors: Haroon Sarblund , Alyamkin Sergey , Shenoy Ramachandra 
Published: November 2018

Abstract
The democratization of artificial intelligence began with the collection of large datasets and the ability to consume them for inferences and prediction by leveraging exponentially increasing computational power. This was further enhanced by the ability to parallel process datasets by breaking them up into independent units and applying fast computation to those units using Graphical Processing Units (GPUs). We discuss one such application in the area of seismic interpretation in the oil and gas sector. Seismic interpretation is particularly suitable since seismic datasets’ characteristics make them inherently amenable to parallel processing in post-stack format.
True big data in the oil and gas sector exists in the seismic arena, where up to one terabyte of data or more can be collected per hour. We show that while preprocessing is required for cleansing and quality checking the data, novel techniques can be applied from the medical and healthcare sectors, namely radiology, for image processing and anomaly detection in images. Further, we also show methods of preprocessing the seismic data, development of seismic images, and novel denoising techniques that lead to the construction of seismic cubes.
3D and 4D seismic cubes post-stack are today amenable to a plethora of neural network based parallel processing methods for anomaly detections. Using such techniques, the achievable speeds to detect anomalies are effectively above ten times what an experienced human being can do. These methods, at their very best, go far beyond human capabilities in terms of processing terabytes to petabytes of data. Such image processing is in use in image recognition, for example, in border control for person identification and verification, and satellite image analysis to discover the minutest of details. We showcase novel techniques based on Convolutional Neural Networks and Deep Neural Networks being utilized for subsurface geological and geophysical properties identification. Further developments of our current and future work are also discussed.
Our presentation specifically describes methods based on Convolutional and Deep Neural Networks to predict faults and salt domes in seismic images. The ability of Deep Neural Networks to continuously learn and self-optimize is the basis of our novel approach. A common criticism of machine learning methods is that most reported results describe results on field data where part of the field data has been used in training the neural network algorithms being used. In the work reported here, we describe the results of our algorithm on two completely blind field data sets – where none of the field data has been used in training the algorithms.
Gravity-Derived Borehole Azimuth through Gravity In-Field Referencing
Authors: Kim Jeong Woo , Rangelova Elena , Kabirzadeh Hojjat , Lee Gyoo Ho , Jeong Jaehoon , Woo Ik , Song Tae Han 
Published: November 2018

Abstract
Safe and economical determination of wellpath in directional drilling is traditionally achieved by the measurement-while-drilling (MWD) method which implements geopotential sensors, i.e., magnetometers and accelerometers. However, inaccuracies in determination of the wellpath arise because of random and systematic errors in measurements. In general, inclination is under good control with gravity measured by accelerometer, while azimuth requires a number of corrections as it also requires magnetic measurement which involves multiple sources of errors such as sensor errors, poorly-modelled crustal magnetic variation, drillstring magnetization, etc. These errors must be completely reduced or minimized to obtain an accurate wellbore position. A magnetic-free system and method to determine a borehole azimuth in the directional drilling is investigated in this study. We show that a borehole azimuth can be properly determined by using a system of coupled accelerometers mounted on measurement-while-drilling (MWD) sensors using Gravity in-Field Referencing (GiFR). In order to reduce errors due to relative oritation of the coupled drillstrings, we developed the Quaternion-based GiRF which considers the relative diaplacements and rotations between the two sets of accelerometer resulting in determining an improved azimuth.
Efficient Utilization of Existing Facilities and Energy in Gas Processing
Authors: Vyas Ajay 
Published: November 2018

Abstract
The objective of the Study was to recommend the most techno-economic option to maximize the NGL Recovery at existing Gas Processing Complex by assessing all the facilities in the complete processing chain from Offshore to Onshore and evaluating the potential options and their associated bottlenecks, production impact and business interruption in order to address the changes in gas supply to the existing Gas Processing Complex from various sources and developments.
The Study was conducted in 3 stages: Feasibility Study was carried out and recommended to install two NGL Recovery Trains with huge capital investment.Gap Analysis and Idea Innovation - The alternative idea of maximizing utilization of existing facilities and energy with minimum modifications was developed by re-distributing the feed streams based on their richness in NGL content within existing facilities so that the optimum NGL Recovery can be achieved.Pre-Feed Study – The developed idea along with other potential options were thoroughly evaluated by a Pre-FEED Study to select the most techno-economic feasible option.
The concept of maximizing utilization of existing facilities and re-distribution of gas according to their qualities offers outstanding benefits to its shareholders: Considerable saving in capital investment ~ 98.64% and energy saving of ~ 18 MWminimum modifications at Offshore Facilities and Existing Gas Processing Complex which could be carried-out during a planned Shut Down and without impacting the production targets.High Net Present ValueReversible design and operationNo long lead items
This paper represents the change in typical approach of installation of new facilities to accommodate the increase in gas supply to a holistic approach of efficient utilization of existing facilities and energy to generate more values to business by generating more revenues with minimum modifications and offering facilities which will be fit for purpose and potential future developments.