bluuebunny/crossref_metadata_2025_split huggingface dataset:
Static and Dynamic Characterization of a Tight Reservoir- A Case-Study from Onshore Abu Dhabi Field
Authors: Agnihotri Praveen , Pandey Vikram , Thakur Parmanand , Al Mansoori Maisoon , Rebelle Michel , Smith Steve , Bhatt Pranjal , Zhunussova Gulzira , Hassan Syed 
Published: November 2019

Abstract
Holistic assessment of project economics and subsurface characterization provides a framework to handle challenging reservoirs. Capturing ranked uncertainties based on their impact on the project and meticulous working towards de-risking the project is key for the success of the entire project. Committing increased production from the field is dependent on proper evaluation of the reservoir.
This paper reviews characterization of a tight reservoir deposited in the intra-shelf Bab basin during lower Aptian time. Initial stage reservoir characterization is critical in formulating reservoir development plan and estimating a realistic assessment of rates and volumes for the field.
The target formation is a low-permeability (average permeability 0.5 mD) heterogeneous carbonate reservoir sitting directly above and adjacent to a producing carbonate reservoir. It is essential to understand communication between the zones. The pilot well is drilled with 225 ft of conventional core and quad-combo logs. Advanced logs such as resistivity image, cross-dipole acoustic, nuclear magnetic resonance, vertical interference test (VIT), formation pressure (including pressure transient data), and fluid samples were acquired. The main objectives of the evaluation program were to determine the formation pressure, collect representative oil sample(s), conduct vertical interference tests between the sub-zones and collect appropriate data for geomechanical and rock-physics characterization.
Thorough pre-job planning and cross-discipline cooperation during the operation provided high fidelity log data and interpretation of the data into a coherent result. This included integration of image data with vertical interference tests from the wireline formation tester (WFT) where barriers were confirmed. In addition, NMR permeability was matched and calibrated using pretest mobility measurements and formation pressure data was combined with full waveform advanced acoustic processing to explain the communication between the upper target zone and the lower producing reservoir. Advanced acoustic analysis helped to fully characterize the target formations with stoneley permeability, azimuthal anisotropy, and presence of fractures.
This paper demonstrates the importance of multi-disciplinary team effort in characterization of challenging reservoirs. It highlights the importance of holistic planning before the execution phase, and keeping a focus on the larger goal while executing individual aspect of a complicated project.
Formation evaluation measurements have evolved over decades and occasionally it benefits the industry to provide a review of how the latest logging measurements fit together in an integrated manner, for successful evaluation of a challenging reservoir.
Application of CNN Deep Learning to Well Pump Troubleshooting via Power Cards
Authors: Zhou Xiangguang , Zhao Chuanfeng , Liu Xiaohua 
Published: November 2019

Abstract
Recent years have seen extensive applications of deep learning, especially in identification and analysis of images, audios and texts, but incipient applications in petroleum industry. Shapes of loops in power cards of a pumping unit are valuable indicators for pump troubles. These troubles may cause engineering accidents, increase operation costs and reduce operation efficiency. This paper applies image recognition technique based on Convolution Neural Network (CNN) to well pump troubleshooting via power cards.
Recent years have seen extensive applications of deep learning, especially in identification and analysis of images, audios and texts, but incipient applications in petroleum industry. Shapes of loops in power cards of a pumping unit are valuable indicators for pump troubles. These troubles may cause engineering accidents, increase operation costs and reduce operation efficiency. This paper applies image recognition technique based on Convolution Neural Network (CNN) to well pump troubleshooting via power cards.
Firstly, we establish mathematical models both for displacements of the polished rod clamp of a pump and for loads of the polished rod during a reciprocating movement, and preset input parameters corresponding to pump trouble types and severity levels. Ideal benchmarking power cards as the media for pump troubleshooting are generated by simulating complete pumping processes via running the mathematical models with the preset pumping parameters.
Secondly, we establish a power card classification model with the AlexNet method. Then we train it with the ideal benchmarking power cards to develop its function of pump troubleshooting and increase the classification accuracy. This model gains robustness and universality from manually presetting parameters for and full coverage of trouble types and severity levels.
Thirdly, we train the classification model with real power cards and obtain the preliminary classification results. A further training makes it more practical and applicable to local operations of pump troubleshooting. In the further training, we localize the ideal benchmarking power cards via manual inspection and local expertiseby adjusting the preliminary classification results honoring field expertise.
Finally, we randomly divide the localized benchmarking power cards into one training set and one testing set, and then train the classification model with the training set and then apply it to the testing set. The final classification results revealthe high accuracy and practicability of the classification model.
It is recommended that GPU should be used for calculation with the classification model to satisfy clients' requirements for higher speeds and efficiency. It provides a feasible method to exploit the potential value of oilfield data assets.
The work in this paper will function as a stepping stone in applying ideas, algorithms and models of artificial intelligence to more extensive and thorough aims.
Overcoming the Challenges of Designing, Developing, and Operating LNG Plants in an Arctic Environment
Authors: Wildman Steve 
Published: November 2019

Abstract
This paper focuses on cost-effectively designing, developing, and operating liquified natural gas (LNG) facilities in Arctic environments. It discusses the inherent challenges associated with engineering, constructing, and operating LNG infrastructure in harsh and highly remote conditions and outlines proven strategies for reducing risk. Specific areas that are discussed include the use of modular design techniques to mitigate overall project risk and drive efficient execution, as well as the deployment of digital tools/technologies for minimizing operating and maintenance costs and maximizing plant availability. For illustrative purposes, the paper discusses the strategies employed on two real-world LNG projects, both of which are located inside the Arctic Circle.
Correlated Friction Reduction and Viscoelastic Characterization of Utilizing the Permian Produced Water with HVFRs during Hydraulic Fracturing
Authors: Ba Geri Mohammed , Flori Ralph , Ellafi Abdulaziz , Noles Jerry , Essman Jacob , Kim Sangjoon , Alkamil Ethar H. 
Published: November 2019

Abstract
Hydraulic fracturing operation requires securing sufficient water resources to access unlocked formations. Successful treatment depends on the fracture fluids that mainly consists of water-based fluid with a low percentage of chemical additives around 1%. Therefore, the oil and gas industry are considered as the largest freshwater consumers by 3 to 6 million gallons of water per well based on a number of fracturing stages. As a result, the traditional water resources from subsurface and surface are getting depleted, and availability of freshwater is becoming more difficult with high cost due to continued demand. For example, operator companies in West Texas face many challenges, including a recent increase from USD 3 to 10 per m3 of freshwater. In addition, transporting process of the raw water to the fracture sites, such as Bakken has an environmental impact, and expensive costs up to USD 5/bbl, while costs of water disposal in range of USD 9/bbl.
This paper aims to study the produced water as alternative water-based fluid with high viscosity friction reducers (HVFR) to reduce environmental footprints and economic costs. To address utilizing produced water as an alternative capable water resource that may use during fracturing treatment, this research presents an experimental investigation associated with using the Permian high-TDS brine water with HVFRs. This work includes experimental research, case studies, and guidelines work on recent improvements on using HVFR to carry proppant and capture the optimum design in fracturing operations. Moreover, the research conducted scaled lab friction measurements that can in turn to be used to improve forecasting of frictions in the field, and therefore of expected surface treating pressures during fracture treatments. Evaluating pipe friction as a function of time to compare HVFRs efficacy in lab and field conditions as well as to predict maximum injection rate during a frac job is investigated.
The outcomes show that high-TDS Permian water with highest dosage of HVFRs had instantaneous pressure reduction effect in 10 seconds while low dosage of HVFRs had lost the effect slowly after 4 min. 30 sec. Also, the results of this study show that the variation of viscosity and pressure reduction at higher shear rate is small. The warm temperature helped rapid polymer dispersion and provided better environment to polymer hydration leads to rapid pressure reduction. Finally, successful implementation in Wlofcamp formation shows that the operation treating pressure reduced from 11,000 to 8,000 psi. The general guidelines obtained can promote the sustainability of using hydraulic fracturing treatment to produce more oil and gas from unconventional resources without considering environmental issues.
Modifying Control Logic to Improve Plant Availability
Authors: Al Dhaheri Abdullah Mubarak , Al Shamsi Abdulla Saeed 
Published: November 2019

Abstract
ADNOC LNG (Train 3) processes HP gas from ADNOC Offshore and the gas goes through a series of processes to remove sulfur & other impurities, gets dehydrated before it is processed to separate the various products and cooled to the prescribed temperature to enable storage and shipping. Apart from LNG, Propane, Butane, Paraffinic Naphtha and Sulphur are also produced as secondary products. The refrigeration of the gas is achieved in two systems namely Propane refrigeration and Mixed Component Refrigeration. Propane refrigeration loop is the heart of the total cooling process in which "Cold Box" is a set of exchangers in series.
The Challenge:
Cold box consists of 12 exchangers/evaporators in series and the process is highly interactive. Disturbance in level of one results in cascading effect on others.
It has been a challenge, during start-up, to stabilize the levels as we had to have substantial manual intervention. Any instrument fault or routine maintenance during normal operation required operator to take multiple level controls in manual to handle the situation.
This had resulted in delayed start-up and poor temperature profile of chillers.
Engineering and Operations teams jointly undertook an initiative to resolve this chronic problem, which was successfully demonstrated post-Train 3 T/A startup in May 2018.
It was jointly agreed to find a solution that would Minimize manual intervention during start-upMaintain stability during normal operationReduce manual interventions in case of instrument failure or calibration
Feed Forward Control Scheme
Implementation of a control scheme in DCS utilizing feed forward action from downstream controllers to upstream level controller. The solution was found simple and robust. Existing software tools available were used effectively to arrive at feed forward constants. Change was implemented during Train-3 Shutdown. A fall back strategy was kept ready – in case new scheme encountered unforeseen difficulties.
Business Benefit
Reduction in start-up time by around 1 Hr. will result in additional production of around 800 Tons of LNG per year which amounts to US$ 257K
Reduced probability of unplanned plant outages. Assuming US$ 1.2 M loss per unplanned shutdown reduction in loss per year comes to US$ 480 K
The DMX Protocol: A New Generation of Geology Driven 3D Discrete Fault and Fracture Network Modelling
Authors: van Dijk Janpieter 
Published: November 2019

Abstract
A new Protocol ("DMX") is presented for 3d DFFN (Discrete Fault and Fracture Network) modelling, a numerical code developed over the last 20 years in order to converge towards a more realistic Discontinuity (fault and fracture) Network representation in space. The protocol introduces the following new features: Fracture interaction, truncation, termination and cross cutting in 3d space based on newly designed collision algorithms and fracture propagation principles; Modelling at any scale range of unlimited basic 3d fracture shapes, specific 3d fracture morphology, and 3d fracture aperture types; A complete integration between classical geological/geomechanical drivers such as stress ellipse, fault zones with 3d slip vectors, and different fold models (axial plane, fold axis and bedding orientation conditioning), geological assembly modelling such as joint spacing and set dependency, offset/faulting, and probabilistic conditioning of any of the parameters and drivers. Examples of the application of the protocol are presented to illustrate few of the unlimited amount of combinations that can be generated in 3d space. Furthermore, an example of the complete flow chart of a calibration to real observed cases is provided. The protocol constitutes a complete game change and opens a range of technological challenges for the future applications in Mining, Civil Engineering and Conventional and Unconventional Oil and Gas Exploration and Production.
From Data to Actionable Insight: Monitoring Fugitive Methane Emissions at Oil and Gas Facilities Using Satellites
Authors: Gauthier Jean-Francois , Germain Stephane 
Published: November 2019

Abstract
Up until recently, the monitoring of greenhouse gases with satellites had been limited to a regional or global scale. Because of the low spatial resolution of scientific satellites looking at gases, attributing emissions to specific facilities had so far not been possible. GHGSat changed that narrative with its first satellite GHGSat-D in June 2016, the first and only in the world specifically designed to monitor emissions directly from industrial sites, with a spatial resolution of less than 50m. The system makes it possible for oil and gas companies to keep a frequent eye on their facilities scattered across vast areas at the lowest cost possible since all measurements are performed remotely with no need to access the sites.
We present recent single pass measurements taken with our demonstration satellite in the Short-Wave Infrared (SWIR) band, showing evidence of point source emission plumes at facilities such as underground coal mine vents and oil and gas facilities.
The lessons learned from GHGSat-D in the last three years making over 4,000 measurements at hundreds of facilities around the world have been incorporated into our second satellite scheduled for launch in August 2019. As a result, GHGSat-C1 is expected to improve on the performance of its predecessor by an order of magnitude. We will present some of the first results from this second satellite.
Finally, we introduce some of the innovative products and applications we are developing using analytics, artificial intelligence and machine learning to better serve our customers with actionable insight and optimize the operation of our system. The ability of the technology to work together with other sources of data (such as other satellites, drones or ground measurements) in an effective tiered monitoring system will also be demonstrated.
Improving Nmr Log Interpretation to Support Mature Field Development, A Case Study Offshore Abu Dhabi
Authors: Yousif Sharifa , Aboujmeih Hassan 
Published: November 2019

Abstract
Nuclear Magnetic Resonance logging measurements (NMR) provide detailed information about rock texture and pore distribution. The main objective of this study is to highlight a carbonate reservoir characterization example in a mature field, offshore Abu Dhabi; providing qualitative porosity, permeability and pore type classification in real time (while drilling), to support efficient field development decision making.
Different logging while drilling vendors tools (NMR-WD) operate at different concepts; some use the longitudinal relaxation time (T1) measurements, others apply the transverse relaxation time (T2). In this case, a low magnetic field gradient (T2) tool type was deployed in a tight formation horizontal oil producer. The well objective is to expose the maximum reservoir contact (MRC).
Primarily, the acquired (NMR) spectrum was used to deliver accurate total porosity, to compute Archie's water saturation. However, delivering a quantitatively reliable permeability become very challenging in the complex carbonate environment subject to study as it was well linked to (NMR) pore size distribution. At first, a standard (T2) cutoff value was applied. The computed (bulk irreducible water – BVI) was too low and hence the permeability was too high, resulting in inaccurate NMR interpretation. Next, a varying T2 cutoff – per zone was applied based on the changing spectrum profile itself. Finally, a Gamma Inversion technique by the service company was introduced to better quantify the different pore types and the corresponding permeability.
The (NMR) log analysis was validated with well core data in addition to production logging results. The data was applied to design the well stimulation and completion programs resulting in a healthy oil producer drain added to the asset.
Integration of Gamma Ray-resistivity-NMR and borehole image logs helped to consolidate the interpretation findings hence supporting decision making for mature field development.
Innovative Biodegradable Intermediates for Sweet Corrosion Inhibitors
Authors: Feche Maxime , Crabtree Alla 
Published: November 2019

Abstract
The corrosion of carbon steel tubing, pipelines and process equipment during Oil and Gas production due to salt water saturated by corrosives gases, such as carbon dioxide and hydrogen sulphide, can lead to substantial environmental and economic consequences. A lot of different technics are used to reduce the corrosion in the pipelines: use of specific alloys, biocides or H2S scavenger. One of the proven and most widely used mitigation techniques is the addition of film-forming corrosion inhibitors into production streams. Those compounds have affinity with metals and will thus form a film at the surface of the metal, creating an electric resistance between the metal and the corrosive species.
The products used offshore and released in the North Sea are currently controlled by OSPAR Convention requiring to meet environmental criteria on three different parameters: Biodegradability, Toxicity and Bioaccumulation. Passing 2 out of 3 criteria is enough to comply with the OSPAR Convention.
This paper presents the performance results obtained with novel biodegradable compositions used as corrosion inhibitors for continuous injection with a thermal stability up to 135°C. A superior performance against sweet corrosion was obtained at 80°C in brines of different salinity, both in the presence and absence of a hydrocarbon phase. Additionally, new compositions exhibit low critical micelle concentrations and their structure can be further modified to adapt to various salinity conditions.
Deformable Micro-Gel for EOR in High-Temperature and Ultra-High-Salinity Reservoirs: How to Design the Particle Size of Micro-Gel to Achieve its Optimal Match with Pore Throat of Porous Media
Authors: Yuan Chengdong , Pu Wanfen , Varfolomeev Mikhail A. , Wei Junnan , Zhao Shuai , Cao Li-Na 
Published: November 2019

Abstract
Conformance control treatment in high-temperature and ultra-high-salinity reservoirs for easing water/gas channeling through high-permeability zones has been a great challenge. In this work, we propose a deformable micro-gel that can be used at more than 100 °C and ultra-high salinity (TDS &gt; 200000 mg/L, Ca2+ + Mg2+ &gt; 10000 mg/L), and present a method for choosing the suitable particle size of micro-gel to achieve an optimal match with the pore throat of core.
First, the particle size distribution of micro-gel was analyzed to decide d50, d10 and d90 (diameter when cumulative frequency is 50%, 10% and 90%, respectively). Core flooding experiments were conducted under different permeability conditions from 20 to 900 mD. The migration and plugging patterns of the micro-gel were studied by analyzing and fitting injection pressure curves together with the change in the morphology of produced micro-gel analyzed by microscope. Finally, a quantitative matching relation was established between the size of micro-gel particles and the pore-throat size of core, its effectiveness was verified by evaluating plugging ability in subsequent water injection process.
The migration and plugging patterns were divided into three patterns: complete plugging, plugging – passing through in a deformation or broken state – deep migration, and inefficient plugging – smoothly passing through – stable flow. The second pattern can be further divided into three sub-patterns as strong plugging, general plugging and weak plugging. Based on the five patterns, a quantitative matching relation between the size of micro-gel particles and the pore-throat size of cores was established by defining three matching coefficients α=d10/d, β=d50/d, γ=d90/d (d is the average pore throat diameter). The effectiveness of this quantitative matching relation was verified by evaluating the plugging ability (residual resistance coefficient) in sequent water flooding process after the injection of 1.5 pore volume of micro-gel. For a strong permeability heterogeneity, the strong plugging is believed to be the expected pattern. The particles size and the pore-throat size should meet the following relationship: 1 &lt; α &lt; 2, 2 &lt; β &lt; 4, 4 &lt; γ &lt;6. In this scenario, the deformable micro-gel particles could achieve both an effective plugging and a deep migration. The quantitative matching relation can provide an indication for the quick determination of the suitable size of deformable micro-gel for conformance control processes in field application, including profile control and water-shut off treatment.