bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating Downhole Temperature Sensing Datasets and Visual Analytics for Improved Gas Lift Well Surveillance
Authors: Bello Oladele , Bale Derek S. , Yang Lei , Yang Don , Kb Ajish , Lajith Murali , Lazarus Sony 
Published: October 2018

Abstract
Given the near ubiquity of fiber-optic, information and communication technologies in reservoir and well management, there is a significant need for one-stop shop downhole distributed sensing data analysis methods together with machine learning techniques towards autonomous analysis of such data sources. However, traditional approaches of converting distributed temperature sensor (DTS) data to actionable insights for optimizing gas lift well operations management remain dependent on training based on human annotations. Annotation of downhole distributed temperature sensor data is a laborious task that is not feasible in practice to train a big data classification algorithm for accurate and reliable anomaly detection of gas lift valves. Furthermore, even obtaining training examples for event diagnosis is challenging due to the rarity of some gas lift valve problems. In gas lift well surveillance, it is essential to generate real-time results to allow a swift response by an engineer to prevent harmful consequences of gas lift valve failure onsets on well performance. The online learning capabilities, also mean that the data classification model can be continuously updated to accommodate reservoir changes in the well environment. In this paper, we propose a novel online real-time DTS data visual analytics platform for gas lift wells using big data tools. The proposed system combines Apache Kafka for data ingestion, Apache Spark for in-memory data processing and analytics, Apache Cassandra for storing raw data and processed results, and INT geo toolkit for data visualization. Specifically, the data analytics pipeline uses data mining algorithms to statistically learn features from the DTS measurements. The learned features are used as inputs to a k-means algorithm and then use supervised learning to predict the performance status of gas lift valves and raise alarms based on analytics-based intelligent warning system. The performance of the proposed system architecture for detecting gas lift valve anomaly is evaluated under varying deployment scenarios. To the best of our knowledge, DTS data analytics pipeline system has not been used for real-time anomaly detection in gas lift well operations.
LEAN Mobile Production Facility to Unlock Marginal Oil Resources
Authors: Poopaiboon Tanthai , Supalasate Phruettiphan , Suebsook Jiranoot , Sakulkaew Sitanun , Surattanasunya Pawin , Eksaengsri Achapan , Charoensawadpong Panunya 
Published: October 2018

Abstract
This paper propose a LEAN design and LEAN approach for project development of Mobile Production Facility (MPF). The Mobile Production Facility (MPF) is the well known facility developed in onshore oil and gas field for mature field which the field development plan has extended to remote areas which contain small marginal oil prospects. The LEAN design for Mobile Production Facility could improve the economics of onshore oil and gas projects development by reducing capital expenditure (CAPEX) and project development lead times and increasing flexibility for production planning through the mobilization design, and be a key factor in the economic exploitation of both marginal and mature fields. Insight gained through in-house design, international code & standard, and package design experts led to the development of the LEAN Mobile Production Facility proposed in this paper. Discussion include a characteristic of a reference oilfield, project background, application of Mobile Production Facility, the innovative design of package and equipment leading to lower CAPEX in detail, as well as the benefits and limitations of the LEAN Mobile Production Facility. Areas of future project development in support of LEAN Mobile Production Facility are identified, including the potential to unlock the further marginal reserves.
Feasibility of Nitrogen Injection in a Multi-layered Lean Gas Condensate Reservoir
Authors: Canchucaja Ramiro , Sueiro Manuel 
Published: October 2018

Abstract
The main objective of this study is to demonstrate in a conceptual fashion the feasibility of change of field development strategy by the use of nitrogen injection in the most north-western section of a lean gas condensate reservoir located in the Peruvian jungle. A reservoir depletion strategy is being taking place since start-up in 2014. This new development is accomplished by turning a producer well into an injector and by installing new processing facilities for nitrogen separation and rejection. A drilling campaign for this new field development is avoided; a fact that places a considerable cost reduction of implementation especially in a location where an offshore-like field development strategy has been adopted.
Dynamic reservoir simulation requires a compositional model for reservoir simulation calculations owing to the nature of the gas condensate fluid that is being produced. Multiple contact miscibility takes place at the nitrogen front so that liquid dropout will be pervasive but in lower degree in one of the formations owing to the difference of composition. This fact is supported by calculations and fluid properties when pressure is even below dew point. A key aspect of nitrogen injection in this field is difference of rock properties between producing formations in a multi-layered reservoir. Therefore, sensitivity analysis is performed to optimize injection and liquid production by assessing well completion, injection flowrate, injection start-up and operational conditions of new surface facilities.
Aspects of the Development of Low-Permeability Gas Reservoirs of Turonian Age
Authors: Kiselyov Anton , Oshnyakov Igor , Melikov Ruslan , Samoilov Mikhail , Korolev Alexander , Loznyuk Oleg 
Published: October 2018

Abstract
Annotation. The article is devoted to the consideration of the prospects evaluation for commercial production of Turonian gas sediments. There are features of geological reserves estimate, field development issues, status of the pilot project the prospects of involving the reserves of the Turonian deposits in full-scale development at the Kharampur field reviewed.
Cloud-Based Solution for Advanced Real-Time Fracturing Evaluation
Authors: Parkhonyuk Sergey , Nikolaev Max , Fedorov Andrey , Konchenko Andrey , Vik Torbjoern 
Published: October 2018

Abstract
The ability to make real-time adjustments to hydraulic fracturing treatment design and pumping schedules leads to more-effective proppant placement and ensures every cluster delivers its full potential. There are numerous advanced methods to monitor and interpret the fracturing downhole events: microseismic analysis, distributed measurements with fiber optics, and high-frequency pressure monitoring. Advances in digital technologies allowed creating a cloud-based application combining downhole and surface data to enable real-time fracturing design adjustments from anywhere.
The application uses a public cloud solutions stack to synchronize surface and downhole measurements and visualize them on the Web. All computations are performed on virtual machines that create the visualization of downhole events in milliseconds. Interpretation of distributed temperature survey (DTS) and heterodyne distributed vibration sensing (hDVS) data has enabled reliable monitoring of diversion techniques, leak detection, and improvements in well integrity and provides support for any type of well intervention. The innovation in the use of the cloud-based application comes from the combination of a novel technique for processing and visualization of high-frequency pressure monitoring (HFPM). HFPM monitoring provides a cost-effective solution for completion efficiency.
The application is currently used for a novel wireline service that utilizes a fiber-optic cable for downhole temperature and acoustics measurements. Results have shown consistency and reliability in the interpretation of received data and confirmation of wellbore events, particularly in DTS and hDVS measurements. Field tests with HFPM have demonstrated that all processing and computations can be reasonably automated in a cloud to provide access to fracturing monitoring at anytime, from anywhere, and from any device. That provides excellent flexibility and means for further reducing the cost of well completions and maintenance, boosting the efficiency, and lowering cost per barrel. A technology stack of a secure public cloud makes an application cost effective and seamlessly scalable on demand. At the same time, the progress of the application does not stop with current possibilities. The innovation of cloud services, such as out-of-the-box machine learning libraries, is now available to for building applications on top of acquired data.
Cloud-based architecture is showing that any digital measurements can be effectively integrated, processed, and visualized in real time for decision making while the job is running. It creates a new service level for real-time fracturing monitoring that differentiates it from previous solutions.
Electrical Discharge Induced ESP Motor Bearing Failure
Authors: Ye Zheng , Wilcox Spencer 
Published: October 2018

Abstract
Motor bearings are a critical component in electric submersible pumping systems (ESP) motors. In many cases, dismantle analyses are unable to identify a definitive root cause for bearing failure. Several hypotheses have been studied to explain motor bearing failures. Some applications experience a higher bearing failure rate than other applications. In this paper, typical motor bearing failure modes will be reviewed, more specifically, the source of shaft voltage and the consequence of bearing electrical discharge failure will be discussed.
During bearing failure root-cause analysis, mechanical components have been the primary focus. Critical thermal expansion coefficients have been verified. The bearing running stress, temperature, eccentricity, film thickness, and lubrication flow have been simulated using cutting-edge finite element analysis (FEA) and computational fluid dynamics (CFD). Results show that in certain material combinations, the incompatibility of the thermal growth of bearing and sleeve material could reduce the running clearance, which would then increase the oil shear loss, and the bearing rubbing. However, tiny pitting has been found in the outside diameters (OD) of cracked bearings returned from the field, with more pitting found on the sleeve ODs. This evidence indicates another bearing failure mode: shaft-induced voltage and bearing electrical discharge.
The direct consequence of electrical discharge is generation of debris, vaporization of motor oil, quenching of bearing/sleeve surfaces, and increase in surface roughness. The debris size (0.001 in.) is larger than the hydrodynamic film thickness and can score the sleeve surfaces due to the loss of oil film protection. The chain of the motor bearing failure due to the electrical discharge is summarized, and this cannot be ruled out in other sizes, bearing systems, or material combinations in an ESP motor. By duplicating the poor power quality conditions, the pitting phenomenon on sleeve is confirmed. Future measurements have been planned to determine the correlation between the power quality and shaft voltage. This paper discusses the risk level for the bearing electrical discharge based the induced shaft voltage.
Electrical discharge bearing damage is a widespread problem that has been studied in other industries since 1992. Electrical discharge / shaft voltage problems can occur on any variable-speed drive motor. The source of electrical discharge through the bearing comes from the voltage potential building from the shaft to the ground (motor housing). However, ESP industries, which produce small motors with multiple rotor sections, have not conducted sufficient analysis to understand this problem. This paper fills the gap to discuss detailed indication evidence and analysis that can be used as a toolbox for motor bearing failure analysis for the ESP industry.
The Integrated Approach to Permeability Adjustment Based on the Simultaneous Well Log and Well Test Interpretation
Authors: Maksimova Elizaveta Nikitichna , Parfenov Nikita Andreevich , Belozerov Boris Vladimirovich 
Published: October 2018

Abstract
Nowadays, efficient field development cannot be imagined without the integrated interpretation of field data with different scale – core, well logs, and formation testers. The above mentioned methods allow definition of permeability values, which can be used during the geological and simulation modeling. However, it should be highlighted that there is no unified approach to permeability adjustment which may lead to unclear connections between absolute gas permeability (core, log) and effective permeability (well test) in reservoir models. As a result correct quantitative description of field development parameters could be questioned.
The present work considers the creation of the workflow for adjustment of core and therefore logs absolute permeability on field values, estimated from formation testing operations. It can be expected that the adjusted permeability values will describe the filtration process more correctly.
During the workflow creation the field with clastic deposits and special logging complex was analyzed. The permeability adjustment workflow, which consisted of several steps, was developed. First of all, absolute log permeability values were obtained taking types/facies into account. Then continuous log effective permeability curves were estimated based on the equations, derived during the analysis of PVT-properties and SCAL data. Finally, the comparison between log and well test permeability was performed.
It has been discovered that the developed methodology can be valid for clastic field with unconsolidated deposits. The transformation from average well test permeability to continuous log effective permeability was mathematically validated. Furthermore, it was shown that estimation of continuous fractional flow values can be performed for several intervals. Besides, calculated log mobility can be used for prediction of layers for which water filtration process can be faster.
The results, which were obtained during the workflow application, are planned to use during further simulation modeling. This can provide the improvement of development process prediction during the simulation modeling and future field development.
Distance-of-Investigation Could be Misused in Unconventional Heterogeneous Reservoirs with Non-Static Properties
Authors: Yuan Bin , Zhang Zhenzihao , Clarkson Christopher R. 
Published: October 2018

Abstract
The concept of distance-of-investigation (DOI) has been widely applied in rate- and pressure-transient analysis for estimating reservoir properties and for hydraulic fracture optimization. Despite its successful application in conventional reservoirs, significant errors arise when extending the concept to unconventional reservoirs. This work aims to clearly demonstrate such errors in the use of the traditional square-root-of-time model for DOI calculations in unconventional reservoirs, and to develop new models to improve the DOI calculations.
In this work, the following mechanisms in unconventional reservoirs are first incorporated into the calculation of DOI: 1) pressure-dependency of rock and fluid properties; 2) continuous/discontinuous spatial variation of reservoir properties. To achieve this, pseudo-pressure, pseudo-time and pseudo-distance are introduced to linearize the diffusivity equation. Two novel methods are developed for calculating DOI, one using the concept of continuous succession of steady-states, and the other using the concept of dynamic-drainage-area (DDA). Both models are verified using a series of fine-grid numerical simulations. A production data analysis workflow using the new DOI models is proposed to analytically characterize reservoir heterogeneity and fracture properties.
The new DOI models compensate for the inability of the traditional square-root-of-time model to capture spatial and temporal variations of reservoir and fluid properties. The pressure-dependency of fluids and reservoir (i.e., fluid density, viscosity, rock permeability and porosity) and reservoir heterogeneities (i.e., deterioration of reservoir quality from the primary fracture to the reservoir), can significantly retard the propagation of the DOI. Another important outcome of this work is to provide a practical and analytical approach to estimate the spatial heterogeneity directly from the production history of field cases.
Pore Volume Compressibility in Shale - Revisited
Authors: Davudov Davud , Moghanloo Rouzbeh Ghanbarnezhad , Lan Yuzheng 
Published: October 2018

Abstract
This study presents a novel method to estimated pore volume compressibility of shale samples based on mercury injection test data. We revisit our previous study (SPE-185059-PA) for more realistic estimation of pore volume compressibility for shale samples. We present a mathematical model to determine accessible porosity and pore compressibility as a function of pressure using Mercury Injection Capillary Pressure (MICP) data.
During MICP testing in a typical shale sample, the rock sample experiences conformance, compression, and intrusion stages as effective pressure increases. By evaluating compression stage, we calculate bulk compressibility. Further by introducing a system of equations, bulk compressibility is decomposed to estimate accessible pore and grain compressibility separately. Different from our previous model, in this study grain compressibility is calculated based on weight average of mineralogy determined from Fourier-transform infrared spectroscopy (FTIR) experiments. Moreover, bulk compressibility obtained from MICP data is compared with the values calculated from ultrasonic velocity measurements. Samples from both Haynesville shale plays are used to perform our study and validate the hypothesis.
Our results indicate that pore compressibility values are higher than anticipated, where calculated values are in the range of 1E-5 1/psi for shale samples at lower pressure. When pressure reaches to 8000 psi, pore compressibility reduces to the range of 1E-6 1/psi in most of the cases. Moreover, when compared with ultrasonic velocity measurements, results indicate that bulk compressibility obtained from MICP is overestimated at lower pressures and slightly underestimated at higher pressures.
The outcome of the paper changes the industry's take on prediction of the reservoir performance, especially the rock compaction mechanism. This study suggests that production owing to rock compaction can be much greater than what has often regarded, which can change the performance evaluation on a great number of reservoirs in terms of economic feasibility.
A Domain Decomposition Approach for Local Mesh Refinement in Space and Time
Authors: Singh Gurpreet , Wheeler Mary F. 
Published: October 2018

Abstract
Reservoir simulations for complex multiphase flow and transport problems often suffer from non-linear solver convergence issues. These manifest in the form of restrictively small time-step sizes even while using unconditionally stable fully implicit schemes. These problems are further compounded when a local mesh refinement is used to accurately represent reservoir parameters available such as permeability, porosity, etc., at multiple spatial scales. We discuss a domain decomposition approach that allows different time-step sizes and mesh refinements in different subdomains (Singh and Wheeler (2018)) of the reservoir that circumvents these issues without compromising computational efficiency and prediction accuracy. This approach extends the well-known methodology of local mesh refinement in space (Wheeler et al. (2002)) to time. Our numerical experiments indicate that non-linear solvers fail to converge, to the desired tolerance, due to large non-linear residuals in a smaller subdomain. We exploit this feature to identify subdomains where smaller time-step sizes are necessary while using large time-step sizes in the rest of the reservoir domain. The three key components of our approach are: (1) a space-time, enhanced velocity, domain decomposition approach that allows different mesh refinements and time-step sizes in different subdomains while preserving local mass conservation, (2) a residual based error estimator to identify or mark regions (or subdomains) that pose non-linear convergence issues, and (3) a fully coupled monolithic solver is also presented that solves the coarse and fine subdomain problems, both in space and time, simultaneously. This solution scheme is fully implicit and is therefore unconditionally stable. The results indicate that using large time-step sizes for the entire reservoir domain poses serious non-linear solver convergence issues. Although using a smaller time step size for the entire domain reduces the convergence issues, it also results in substantial computational overheads. The proposed space-time domain decomposition approach, with smaller time-step sizes in a subdomain and large time-step sizes everywhere else, circumvents the non-linear convergence issue without adding computational costs. Additionally, a space-time monolithic solver renders a massively parallel, time concurrent framework for solving flow and transport problems in subsurface porous media. Since the proposed approach is similar to the widely used finite difference scheme, it can be easily integrated in any existing legacy reservoir simulator.
Smart Oilfield Safety Net - An Intelligent System for Integrated Asset Integrity Management
Authors: Saeed Muhammad Rizwan , Chelmis Charalampos , Prasanna Viktor K. 
Published: October 2018

Abstract
In smart oilfields, a large volume of data is being generated related to assets, personnel, environment, and other production and business-related processes on a daily basis. Storing vast amounts of data is only justifiable if it leads to the discovery of actionable insights which can then be translated into improvements in operational efficiency and Health, Environment, and Safety (HES) conditions. Smart oilfield data is of high volume, variety, and velocity and can be located in multiple data silos. This presents an urgent need to develop scalable and extensible techniques that can enable domain experts to access data and perform analytics to yield better decisions and results. The focus of this paper is on the process of Asset Integrity Management and the role of Semantic Web technologies for significantly improving decision-making in this domain. The most significant challenges, thus, are to manage the high volumes of data, create a holistic view of asset integrity data, allow intuitive access to the data, and generate insights through an agile system that can be utilized by domain experts without requiring extensive assistance from IT experts. For this, we present the Smart Oil Field Safety Net (SOSNet) system, a Semantic Web-driven platform, that performs integration of asset integrity data, provides simplified querying mechanism for accessing the integrated data and facilitates analytics on top of it to improve efficiency and robustness of the process of Asset Integrity Management.