bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning of Spatially Varying Decline Curves for the Duvernay Formation
Authors: Bakay Alexander , Caers Jef , Mukerji Tapan , Miller Patrick , Cartier Cheryl , Briceno Arnulfo 
Published: September 2019

Abstract
The focus of this paper is on Duvernay shale formation in Alberta, Canada. The objective is to provide, based on existing data of production, completion and geological parameters, an automated machine- learning approach to determine the spatial variation in decline type curves for gas production. This model will enable the prediction and uncertainty quantification of production profiles for new target wells or areas in the basin.
The project is based on publicly available monthly production data from most of the producing wells of the Duvernay formation. We use k-means to cluster 273 wells, using geological parameters (thickness, porosity, etc.), completion parameters (horizontal section length, proppant volume, etc.), spatial location, fluid window, and production curves. Based on the clustering results, a machine learning classification is used to draw distinct geographic regions, within which the combination of geological, completion, and production factors is fairly similar. A support vector machine approach is used to create maps of clusters and quantify its uncertainty.
In addition, functional classification and regression trees (CART) is used to indicate the most important/sensitive factors that should be used for clustering.
The results show that the unsupervised method, k-means, performs equally as well as the supervised CART method. The methodology is flexible and allows for quick changes in the variables used in clustering; the transfer to another dataset or basin is straightforward.
Advanced Real-Time Analytics Allow Performing the Shallowest Injection Test Ever on the Norwegian Continental Shelf NCS – Rational, Planning, Execution and Results
Authors: Stueland Eirik , Øverland Alf M. , Persaud Mira , De Leonardis Donato , Sanfilippo Francesco , Santarelli Frederic J. 
Published: September 2019

Abstract
Reservoirs in the Barents Sea are several times shallower than in other parts of the NCS, essentially due to recent uplift and erosion of younger sediments. A proper understanding of their geomechanics is considered paramount for their successful development. In turn, the lack of any available analogue makes the proper in situ measurement of key parameters compulsory.
The paper describes the planning and execution of an appraisal well solely dedicated to the purpose of geomechanics data acquisition in the shallowest oil reservoir on the NCS – i.e. coring, logging, XLOT and injection testing. It focuses on the operations conducted in the oil reservoir itself, which included an entirely novel multi-cycle injection test aimed at estimating the large-scale thermal stress coefficient of the formations around the well – i.e. the impact of the injection temperature on the fracture pressure of the formations.
Every operation in the well was challenging due to the sea depth being about twice that of the overburden thickness and to the formations being quite consolidated, which was met by careful iterative multidisciplinary-planning. The equipment was often taken to its limit and sometimes extended beyond its standard use – e.g. the metering systems.
The injection test itself could not be performed traditionally – i.e. use of surface data and downhole memory gauge. Instead, the downhole gauge data were sampled, pumped out and transferred to a remote site where real time advanced analytics was used to ensure that safety criteria were always met throughout the operation in terms of vertical fracture propagation and lack of reservoir compartmentalisation. In addition, this allowed adjusting the planned injection schedule to the exact formation's response, which could not be fully quantified ahead of time.
All the targets of the appraisal well were met. The injection test – i.e. the shallowest on the NCS and perhaps worldwide in an offshore environment – was performed successfully. Its main results are considered essential for a possible future field development – e.g. the injectivity is confirmed and, in addition, a significant thermal effect is proven.
The series of novel technologies deployed in the extreme environment presented in the paper can easily and beneficially be extended to more traditional reservoirs. This concerns performing multi-cycle injection tests on appraisal wells on a systematic basis to prepare and optimise the development plan, real-time monitoring through advanced analytics and adjustment of these tests, start-up of injection wells during field development, monitoring and optimisation of water injection schemes, etc.
Effect of Asphaltene Precipitation and Deposition on Miscible Viscous Fingering in Porous Media — High-Resolution Nonlinear Numerical Simulations
Authors: Sabet Nasser , Mohammadi Mohammadjavad , Zirahi Ali , Zirrahi Mohsen , Hassanzadeh Hassan , Abedi Jalal 
Published: September 2019

Abstract
This work focuses on modeling the miscible viscous fingering in porous media accounting for asphaltene precipitation and deposition. The mass balance equations for solvent and asphaltene are defined, and the highly nonlinear system of equations is solved numerically through hybridization of compact finite difference and pseudo-spectral methods. We explain how asphaltene precipitation and the resulting formation damage influence the growth of viscous fingers.
To conduct our analysis, we use the experimental data for the amount of asphaltene precipitation at different solvent mass fractions and also oil viscosity at various asphaltene and solvent contents. This data is measured in our lab and is used as input for the nonlinear numerical simulations. For these simulations, the conventional finite difference schemes cannot be applied as they suffer from the excessive computational time and most importantly, numerical dispersion. Therefore, we employ hybrid techniques to benefit from the high accuracy of spectral methods and capture the nonlinear dynamics of fingerings on very fine grids.
Hydrocarbons such as light n-alkanes are widely used as diluents in the production and upgrading of heavy oils. The addition of a diluent to heavy oil or bitumen alters the chemical forces acting within the mixture, leading to the precipitation of asphaltenes. It is hypothesized that precipitation of asphaltene from oil changes the viscosity behavior of the mixture, influences the dynamics of viscous fingering, and therefore affects the oil recovery. Moreover, asphaltene deposition alters the porosity and permeability of the porous media and might modify the flow paths, leading to possible formation damage. Our results show that asphaltene precipitates are mostly accumulated in the contact interface between the solvent and oil. The major asphaltene deposition occurs along the growing fingers leading to permeability reductions up to 30% in the studied cases.
In-Depth Understanding of the Ultra-Low-Interfacial-Tension Foam Flood in Oil-wet Fractured Media through Simulation with an Integrative Mechanistic Foam Model
Authors: Luo Haishan , Mateen Khalid , Ma Kun , Ren Guangwei , Neillo Valerie , Blondeau Christophe , Dong Pengfei , Puerto Maura , Biswal Sibani , Hirasaki George 
Published: September 2019

Abstract
Recovering oil from oil-wet matrix in fractured carbonate rocks is highly challenging. Recent experiments have indicated that ultra-low-interfacial-tension (ULIFT) foam flood could significantly boost the oil recovery from such rocks. However, there is limited information available about the foam and the microemulsion transport in the fractured system to extract the oil from low permeability matrix. Adaptation of this technology in the field would not be possible without a good understanding of the process.
The aim of this work is to model and history match the ULIFT foam flood in fractured carbonate cores for further gaining insight into the complex four-phase flow. The model was set up based on a group of experiments using cores split lengthwise to simulate axially confined fractures. Pre-generated foam was tested in this system due to the lack of in-situ generation of foam in the straight fracture at the core scale. Various foam coalescence mechanisms, with/without oil, were modeled, and a dynamic-texture population-balance foam model was developed for this purpose.
Our model incorporates the effects of oil and permeability as well as the coexistence of foam and microemulsion on the foam apparent viscosity. The model is able to reasonably well history match both the oil recoveries and the total pressure drops of the ULIFT foam floods in fractured carbonate cores. More impressively, the modeling results agree very well with the pressure gradient of each section of the core, indicating that the spatial variation and distribution of the foam texture are largely captured. The simulation results also show that the pre-generated foam greatly resists the fluid flow in the fracture close to the injector side and enhances the diversion of injected fluids into the matrix layers, leading to improved oil displacement. The resulting oil crossflow from the matrix to the fracture destabilizes the foam at the foam front thereby slowing the transportation of foam in the fracture. Additional case studies suggest that significantly more oil can be recovered if the foam destabilization by oil could be reduced/mitigated.
Test results disclosed in this paper demonstrate for the first time the successful modeling and history-match of ULIFT foam floods in fractured rocks. Valuable insight into this complex process has been gained through this innovative research. This is of great value with respect to the further optimization of the corefloods, the design of the surfactant formulation, and the feasibility of applying this new technology to the field scale.
Large Deployment of Multiphase Flowmeters in an Unconventional Field
Authors: Theuveny Bertrand , Moncada Katharine , Roth Melissa , Wu Yvette , Mikovich Michael , Guichard Anna 
Published: September 2019

abstract
The need for monitoring individual well production in unconventional fields is rising. The drivers are primarily related to accurate reporting for production allocation between wells. The main driver in North American operations for a meter-per-well flow rate monitoring has been the need for accurate per well production accounting due to the complexity of the land-owner interest.
There are additional benefits from the monitoring of early decline and determination of the transient evolution of the reverse productivity index (RPI) to evaluate the well performance. The availability of long-term rate transient data supports decline analysis and rate transient analysis, leading to better understanding of the estimated ultimate recovery (EUR), which may drive the selection of infill drilling locations. Finally, the identification of interference between flowing wells can help mitigate the issues of parent/child wells.
A specific case in the Eagle Ford is the systematic deployment of full gamma-spectroscopy multiphase flowmeters at well pads. This intelligent pad architecture consists of one multiphase flowmeter per well and a production manifold that enables commingling of the production to a single flowline connected to the inlet manifold of the production facility.
The rationale of the decision for the installation of such solution in lieu of a metering separator per well is based on the evaluation of the impact of this technology on capex and opex reductions.
Several lessons learned are provided. They include a discussion of the change management issues related to the installation of the meters, the modifications necessary to the production facility at the receiving side, and the data management and data analytics that were enabled from the gathering of systematic, continuous, and high-resolution measurements.
The impact of the installation of the meters in the field is noticeable and quantifiable. with several prior wells used as a benchmark. The effects are not limited to cost reduction, but also lead to an increase in production related to the release of operational crews from daily well testing tasks that used to be necessary. The data quality and coverage are also increased.
A few suggestions are made concerning optimization of the deployment and use of remote monitoring options for enhanced efficiency. Automated data workflows are also discussed.
The reduction of HSE risks through a better management of field operators is also assessed.
Directional Measurements While Drilling
Authors: Karvinen Kai , Hoehn Oliver , Schulze Steffen , Wassermann Ingolf 
Published: September 2019

Abstract
Real-time downhole estimation of inclination and azimuth is desirable for improved wellbore quality, better management of the drilling process with regard to wellbore hydraulics and drilling dynamics, and is a prerequisite for advanced directional drilling services such as downhole azimuthal hold mode and surface-based automated trajectory control. However, reliable estimation of azimuth while drilling remains a challenging problem, particularly in certain orientations in harsh drilling environments. We present a detailed problem description and describe the approach used to develop a new algorithm to estimate azimuth while drilling, which offers significant improvements over existing algorithms. Such an algorithm will form the foundation for advanced drilling system automation services, such as automated trajectory drilling.
Validation of the Utility of the Contrast-Agent-Assisted Electromagnetic Tomography Method for Precise Imaging of a Hydraulically Induced Fracture Network
Authors: Ahmadian Mohsen , LaBrecque Douglas , Liu Qing Huo , Kleinhammes Alfred , Doyle Patrick , Fang Yuan , Jeffrey G Paine , Lucie Costard 
Published: September 2019

Abstract
Characterizing hydraulically induced fractures—height, length, orientation, and shape—is key to understanding reservoir performance. Our previous work has focused on the comparison of the state-of-the-art geophysical techniques currently used in hydraulic fracture imaging (microseismicity, tracer, tiltmeter, and distributed acoustic and temperature sensors) to perform a comprehensive set of electromagnetically active proppant (EAP)–assisted tomography methods (LaBrecque et al., 2016; Ahmadian et al., 2018). In our latest study, we conducted a field pilot at The University of Texas at Austin Bureau of Economic Geology's Devine Test Site, located approximately 50 miles southwest of San Antonio, Texas. Following hydraulic fracturing with EAP, we detected a measurable electromagnetic (EM) fracture anomaly at a depth of 175 ft (~53 m) by use of a set of four PVC-cased wells equipped with electrode arrays for single hole, hole-to-surface, and cross-hole electrical resistivity tomography. Because of relatively low overburden pressure, and as designed, fractures grew horizontally and appear nonaxisymmetric about the center injection well (fracture image looks like a human foot). This design allowed us to verify our results with drilling and logging of eight vertical wells. In addition, we cored two wells, and these samples further corroborated the presence of EAP proppants at the predicted depth. Together, these results conclusively corroborate the accuracy of our EM inversion models to within 5 ft of the physical edge of the EAP-filled fracture anomaly. We are currently using results from our ongoing geophysical surveys to refine and verify the efficiency of forward and inverse EM modeling codes for open-borehole and through steel casing scenarios. This paper describes the ground-truth validation of our model predictions, as well as the future direction of our research.
First Digital Intelligent Artificial Lift Production Optimization Technology in UAE Dual-String Gas Lift Well - Business Case and Implementation Plan
Authors: Alshmakhy Ahmed , Al Daghar Khadija , Punnapala Sameer , AlShehhi Shamma , Ben Amara Abdel , Makin Graham , Faux Stephen 
Published: September 2019

Abstract

Objectives/Scope
Majority of the world's gas lifted wells are under-optimized owing to changing reservoir conditions and fluid composition. The gas lift valve (GLV) calibration is required with changing conditions. Apart from that, an allowance needs to be kept so that the valve change remains valid for longer time. Compounding this, when adjusting gas lift parameters, it was not easy for the gas lift operator to make data-driven decisions to assure continuous maximized production. These challenges are further amplified with dual completion strings: fluctuating casing pressure; unpredictable temperatures due to the proximity of the two strings; and inability to individually control the injection rates to each string. String dedicated to the formation with lower productivity and reservoir pressure tends to "rob" gas from other string. Operating philosophy in such cases end up producing from one string. Production optimization in such cases requires frequent intervention with attendant costs and risks thus presents an opportunity to re-imagine gas lift well design.

Methods, Procedures, Process
ADNOC in collaboration with Silverwell developed a Digital Intelligent Artificial Lift (DIAL) system, which consists of multiple port mandrels to be placed at GLV depths. These mandrels are connetced to the surface operating system with a single electrical cable. The ports can be selectively opened or closed by sending an electric signal from the surface unit. In addition, pressure and temperature sensors are also placed which help record these parameters in real time. Such a system enables the choice of depth, injection rate, loading and unloading sequence controlled from the surface. Realtime optimization is possible as pressure/temperature data helps draw accurate gradient curves. This system makes gas lift optimization possible in dual gas lift wells.

Results, Observations, Conclusions
It has been estimated that this technology delivers a production increase approaching 20% for single completion wells, and exceeding 40% for dual-string gas lifted wells. Recognizing this opportunity, a business case and implementation plan were developed to pilot a dual-string digitally controlled gas lift optimization system.

Novel/Additive Information
This paper will describe, the screening phase, business case preparation, risk assessment and validation process, leading to this 1st worldwide implementation of a fully optimized dual completion gas lifted well. Implementation plan of novel digital gas lift production optimization technology in an onshore dual completion well. The completely original approach increases safety, efficiency, operability and surveillance.
Machine Learning Forecasts Oil Rate in Mature Onshore Field Jointly Driven by Water and Steam Injection
Authors: Kubota Leonardo , Reinert Danilo 
Published: September 2019

Abstract
In this paper, we tackle an old problem – production forecast - using techniques that are relatively new to the reservoir engineer toolbox. The problem at hand consists of forecasting oil production in a mature onshore field simultaneously driven by water and steam injection. However, instead of turning to traditional methods, we deploy machine-learning algorithms which will feed on a plethora of historical data to extract hidden patterns and underlying relationships with a view to forecasting oil rate. No geological model and/or numerical reservoir simulators will be needed, only 3 sets of time-series: injection history, production history and number of producers. Two Machine-Learning algorithms are used: linear-regression and recurrent neural networks.
Industrial Scale Demonstration of Ceramic Membrane Filtration for Produced Water Treatment
Authors: Ishikawa Fuyuhiko , Mima Satoru , Nakamura Arata , Shinohara Masayo 
Published: September 2019

Abstract
Water production from oil and gas fields has been more and more increasing globally, and thus the treatment and the reuse of produced water has become one of the top issues in oil and gas industry. Produced water re-injection (PWRI) to reservoirs for pressure maintenance or water flooding is an environmentally-friendly scheme over disposal options. Because solid particles, bacteria, as well as residual oil can cause plugging of the pores in the formation rock resulting in deterioration of oil recovery, PWRI to "tight" or low permeable reservoirs requires high levels of removal of these constituents. In addition, there is also a growing interest of removal of dissolved salts from the produced water for the beneficial reuse. This also requires an advanced filtration as pretreatment to desalination by reverse osmosis (RO) or evaporation. For both of these applications, microfiltration (MF)/ultrafiltration (UF) technologies using ceramic membranes are considered as a very effective solution because ceramic membranes offer high hydrophilicity, relatively low fouling by oil-in-water, and broad chemical and thermal compatibilities. An industrial scale produced water treatment demonstration plant has been installed in an oilfield to test the performance of ceramic MF membranes. The plant includes a crossflow filtration system which accommodates commercial ceramic membranes (180mm Dia., 1,500 or 1,000mmL) followed by RO equipment. The demonstration test was performed for seven months in 2017. Through the seven months of the field demonstration, protocols for sustainable operation were developed under field conditions in which feed water qualities varied very widely in terms of concentration of oil & grease and other foulants. The filtrate contained suspended solids (SS) and oil & grease not higher than 1 mg/l and 10 mg/l, respectively, at all times during the test period. Therefore, it has been proven that the ceramic membrane filtration can be very effective for alleviating plugging risk when applied to PWRI in tight reservoirs. Silt-density-index (SDI) of permeate, an indicator of RO feed water quality was not higher than 3.0 and the average was 1.6; this indicates the membrane-filtered water is appropriate for the RO feed.
Application of Multiphase-Multilayer Pressure Transient Analysis for Well Monitoring and Reservoir Management - A Case Study of Deep-Water Offshore GoM Reservoirs
Authors: Ajayi Arashi , Fassihi Reza , Wrobel Adam , Allouache Aimon , Johnson Mark , Bryant David , Akajagbor Collins 
Published: September 2019

Abstract
Well diagnostics in deep, offshore GoM are vital in order to interpret any issues related to productivity losses. This is especially important since any intervention in such wells is very costly. Multiphase flow is amongst leading causes of well productivity loss. This paper presents an integrated workflow that provides a solution to the challenge of quantifying multiphase PTA results in single and multiple commingled production cases. The workflow is used to monitor the performance of several wells over an extended period in a deep-water offshore reservoir under water/aquifer drive. It builds on a succession of PTA tests starting from single phase flow until water breakthrough and beyond. The results of historical PTA provided meaningful insights that were used as basis for actions that led to well and reservoir performance optimization.