bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Fundamental Model for Wormhole Formation Including Multiphase Flow
Authors: Cheng Haoran , Schwalbert Mateus Palharini , Hill A. Daniel , Zhu Ding 
Published: April 2019

AbstractThe industry has been developing numerical models to simulate the wormholing phenomenon in carbonate matrix acidizing, both to save cost and time with experiments and to upscale the laboratory results to the field scale. The Two-Scale Continuum Model is a fundamental model that has been successfully used for this end. Previous studies with this model only simulated single-phase flow: injection of acid into a water saturated rock. However, significantly different behavior is observed experimentally by injecting acid into oil or gas saturated cores. In this work a fundamental multiphase model for wormhole formation is presented using the two-scale continuum approach, allowing the simulation of the wormholing for acid injection into oil or gas bearing rocks, with different saturations.The two-scale continuum model represents the fluid flow and acid transport in the porous medium in the Darcy scale, but calculates the acid-rock reaction with dissolution of the rock in the pore scale. This model was implemented in transient three-dimensional anisotropic form. Each different phase occupies a volume fraction in each grid block, defined by the porosity and fluids saturations. The fluid flow is calculated by solving the Darcy-Brinkman-Stokes equation, where the relative permeabilities are functions of the saturations. The acid transport and reaction equations are solved, and as the acid injection proceeds and the rock is dissolved, the porosity increases in the grid blocks where dissolution occurs. The pore properties such as permeability, pore radius, and specific surface area are updated as porosity evolves, being upscaled from pore to Darcy scale. The simulation keeps track of the different fluid phases by calculating the saturations using the Implicit Pressure Explicit Saturation (IMPES) method.The developed model was implemented in an open source Computational Fluid Dynamics package and validated against experimental data. For the validation, the adjustable parameters in the model were calibrated so that the simulation results represent the different dissolution patterns and correctly reproduce the acid efficiency curves obtained experimentally. The same calibrated model was used to simulate the core flooding experiments with water and oil saturated cores. The dissolution patterns (face dissolution, conical wormhole, dominant wormhole, etc) and acid efficiency curves predicted by the new model match the experimental data. Other simulations presented include the shift in the acid efficiency curves observed for different oil viscosities, residual oil saturations, and different water saturations.To the authors’ knowledge, this is the first two-scale continuum model to simulate wormhole propagation including multiphase flow. With adequate history match, it was shown to accurately predict the acidizing results for different fluid saturations, as observed in experiments.
KPI Based Standardizing Static Geomodeling Practices for QA and QC of Models
Authors: Dhote Prashant , Al-Adwani Talal , Al-Bahar Mohammad , Al-Otaibi Ahmad , Chakraborty Subrata , Stojic Slobodan 
Published: April 2019

Abstract
Subsurface petroleum industry is burdened with uncertainties in every aspect from exploration to production due to limitations of accessibility to reservoir and technology. The most important tools used to understand, quantify and mitigate the uncertainties are geostatistical static modeling and numerical dynamic simulation geomodels. Geomodels are widely used in the industry for characterizing the reservoir and planning favorable development strategy. It is vital instrument for maximizing asset value and optimize project economics.
Static geomodels are foundation for all the advanced numerical and analytical solutions to solve the intricacies of reservoir performance. At the same time, it is where all the static and dynamic geological and engineering observations get integrated to develop common understanding of the reservoir for future studies. Understanding of the above observations and imaging of reservoir framework by individual is the basis for building static geomodels. Hence, at time, the process is highly subjective and proper QC'ing of the models to achieve the general and specific modeling objectives becomes imperative. Simple Questionaries’ based QC'ing and ranking methodologies are also controlled by subjectivity and individual preferences.
In the present endeavor, quantitative ‘Key Performance Indicators (KPIs)’ based standard static geomodeling practices and QC'ing methodologies at corporate level are developed in specially designed "Process Implementation Project (PIP) – Hydrocarbon resource and Uncertainty Management"’ under the aegis of ‘Kuwait Oil Company (KOC) - Reservoir Management Best Practices Steering Committee'.
The main objectives are to establish a practical modeling process, workflows and criteria to standardize modeling processes. A structured self-guidling modeling document has been developed with self-assemment guidelines and questionary. Finally, for each individual process a set of KPIs are specified as minimum standard to meet to obtain the approval of static model.
The present efforts are important for any geologists, geomodelers and reservoir engineers dealing with geostatistical and numerical reservoir modeling and will provide the KPI's based general practices for quality assurance (QA) and QC'ing of the models.
Benchmarking of State-of-the-Art Assisted History Matching Methods Under Reservoir Uncertainty on a Complex Water-Flooding Process
Authors: Maucec Marko , Saffar Ali , Turki Ali , Fahmy Ismail 
Published: April 2019

AbstractIn this paper we present the framework and results of a benchmarking study to validate performance of conceptually different methods for computer-assisted history matching (AHM) under reservoir uncertainty on an example of complex waterflooding process.Traditionally reservoir models were manually reconciled with production data, relying mostly on workflows based on engineering judgment and established best practices. The main disadvantage of the manual HM process is that the reservoir simulation disengages from the geological model and fails to quantify reservoir uncertainty. The oil and gas industry has advanced in developing methods for AHM that enable producing geologically-consistent reservoir simulation models with robust uncertainty quantification and high predictive value. In our study we build distinctive, computationally-intensive AHM workflows covering global multi-objective stochastic optimization and streamline sensitivity-based inversion to perform dynamic real-field model update and history matching.We use the model of faulted reservoir under a waterflooding improved oil recovery regime. A comprehensive geo-modeling workflow incorporates facies, petrophysical properties, and saturation height function with uncertainty quantification performed on rock types, porosity, permeability, Kv/Kh, water saturation and fault transmissibility. During dynamic model update, the uncertainty workflows were executed as data assimilation on the sufficiently diverse prior ensemble of geomodel realizations, and as a Closed (Big) Loop process, where geomodel realizations are parameterized and updated simultaneously (on-the-fly) using global optimization. The misfit function, subject to minimization, incorporates oil and water rates and static wellhead pressure.The study concludes that different AHM techniques demonstrate different convergence performance. The overall success dramatically depends on the uncertainty quantification of the initial geomodel. Practical reservoir simulation times were achieved through utilization of a Massive Parallel Processing deployed on an HPC cluster. However, most importantly we demonstrate that, by deploying advanced AHM workflows, the updates of geologically and structurally complex models, with tens of millions grid-cells and large number of matched wells can render geology well-conditioned realizations, without necessity of introducing non-geological features in order to achieve a satisfactory match. Thus, the validated practices add a tangible business value to the process of integrated reservoir modeling by delivering a robust simulation model with high predictive value for future field development planning.
Experimental Investigation on Wellbore Strengthening Mechanism and Tight Fracture Plugging Drilling Fluid Based on Granular Matter Mechanics
Authors: Liu Junyi , Guo Baoyu , Qiu Zhengsong 
Published: April 2019

Abstract
With the promotion of oil and gas development around the world, the exploration scope has been gradually extended to complicated geological reservoirs, such as deep or ultra-deep, unconventional, deep-water reservoirs, and lost circulation and wellbore instability have been becoming the most serious problems, which puts forward higher requirements on the drilling fluid technology. In order to solve these technical problems, the wellbore strengthening mechanism, tight fracture plugging methods and simulation experimental method for drilling fluids were studied respectively in this paper.
Firstly, the wellbore strengthening mechanism of the stress cage method that improves wellbore pressure containment was firstly investigated based on ABAQUS finite element modeling analysis. It was found that wellbore pressure containment could be improved by enhancing plugging performance of drilling fluids to plug and prop natural or induced fractures to eliminate fracture propagation and increase hoop stress. The key performance of loss prevention materials has been proved to play a prominent role to achieve wellbore strengthening effect and strengthen the wellbore. According to the basic principle of "force-chain" in granular matter mechanics, the key fine technical indices were proposed to evaluate the particle strength, particle resiliency and surface friction of loss prevention materials. Meanwhile, the corresponding physical model of tight fracture plugging zones was established to reveal the tight fracture plugging mechanism at micro scale and the optimization method of tight plugging drilling fluids was also put forward, and it was concluded that using reasonable particle type, particle size distribution and concentration control, rigid particles, resilient particles and fibers were synergized to plug fractures, so as to form tight pressure containment plugging zones with a strong force chain network and greatly improve the wellbore pressure containment.
The novel experimental apparatus for evaluation and dynamic simulation on the plugging characteristics of drilling fluids was developed, which could simulate the loss and plugging process of fractures with different openings under different formation pressures and temperatures. Using this novel experimental apparatus, the strengthened tight plugging formulas were also optimized for drilling fluid at the wedge fractures with different widths, which exhibited tight plugging characteristic self-adapting to different openings with pressure resistance up to 8MPa, thus improving loss-prevention ability of drilling fluid and significantly enhancing wellbore pressure containment of subsurface formation.
A New Reservoir Prediction Method Based on Geological Seismic Conditioning for Complex Barrier Island and Its Application at H Oil Field
Authors: Chen Xin , Zhang Suhong , Ou Jin , Ye Yufeng , Xu Lei , Ma Yingze , Wei Xiaodong , Yang Ke , Chen Gang , Zhou Guofeng , Xia Yaliang , Yan Xiaohuan , Zhang Zeren , Liu Jingluan , Zhou Xiaoming 
Published: April 2019

Abstract
In order to improve the accuracy of reservoir prediction results, the conventional method usually include seismic inversion, and seismic attribute analysis. Due to the limitation of the vertical resolution of seismic data, it is hard to identify the thin reservoir by seismic attributes directly. In order to improve the prediction accuracy of reservoir, this paper show a new reservoir characterization technique based on geological seismic conditioning. The new method mainly includes five steps. The first step is sedimentary facies classification based on the geological seismic analysis, such as core data, thin section analysis, FMI logging, NMR logging and conventional logging. The second step is modern sedimentary model optimization and forward modelling. In order to establish a reasonable sedimentary facies model, a similar barrier island modern sedimentary model was chosen. To understand the geological significance of seismic data, two different dominant frequency were designed for forward modelling based on the sedimentary facies model and petrophysical analysis. The third step is seismic conditioning under the guide of sedimentary facies model forward modelling. The next step is seismic constraint stochastic inversion, and the last step is reservoir characterization and new well confirm. The application of this method in A oilfield shows that the techniques not only improved the identification ability of the reprocessing seismic data, but also improved the prediction accuracy of the reservoir characterization results. This new reservoir characterization technique can integrated multidisplinary information, such as modern sedimentary model, well data and seismic data, to establish a reasonable sedimentary model, to enhance the resolution of seismic data by conditioning, and get an reasonable reservoir characterization results based on the seismic inversion.
Integrated Multi-Disciplinary Analysis on Flow Characteristics in Transition Zones: Case Studies in Offshore Malaysia
Authors: Marzuki Izral Izarruddin Bin , Masoudi Rahim , Murugesu Thanapala Singam , Ranjan Rakesh , Johare Dzulfadly 
Published: April 2019

Abstract
Transition zone (TZ) refers to a certain height above the Free Water Level (FWL) where both hydrocarbon and water could potentially flow together. The two phases flow is not the definite situation based on the actual fields’ performance observation and it is an ongoing common misunderstanding with broad level of subjectivities for years. Lack of relevant experimental data and the insufficient physical understanding of the characteristics of the transition zone makes the modeling of both 3D static and dynamics to be challenging, subjective and finally uncertain when it comes to predictive capability.
The recent studies by the team and this paper aim to illustrate that in the transition zone due to the relatively lower capillary force, oil has usually occupied the bigger pores compared to the intervals above the transition zone and hence the oil is more prone to move. Also, under enough drawdown and differential pressure level where it could be sensed by aquifer, water could also be fed by aquifer through the established water film by capillary. However, the water saturation in the transition zone will not be reduced through production compared to the initial water saturation. Hence, the relative permeability curves should be cautiously developed to represent the flow condition in the transition zone.
Three oil rim developments in Malaysia with established transition zone and enough production & relevant surveillance history have been selected for this study. There is evidence from actual production data on dry oil recovery from transition zone between one to two years after those wells were put into production. Depending on the standoff of bottom perforated interval with oil water contact (OWC), water production onset may vary with time. Some of the fields have been placed with several horizontal wells in tapping the oil within transition zone to maximize recovery.
This paper will discuss an integrated multi-disciplinary views on understanding the flow characteristics and dry oil production from transition zone. Understanding the capillary pressure, depletion and drawdown strategy together with well completion design as well as location in respect with height above Free Water Level (FWL) is crucial in successful monetization of the transition zone.
Oil Detection Based on Layer Buried-Depth Corrected Elastic Inversion in Deepwater of the Pearl River Basin
Authors: Liu Xumin , Chen Zhaoming , Liu Hao , Zhang Wenzhu 
Published: April 2019

Abstract
Because of the high drilling expense and fewer wells having been drilled in Deepwater of the Pearl River Basin, the complexity and difficulty of oil and gas exploration in this area always restrict our development procedure. In order to overcome these problems in oil and gas exploration, this paper will propose a comprehensive and feasiable approach, which makes full use of both well logging data and seisimic data and combine techniques of rock physical modelling and seismic pre-stack inversion. Such a well-orgnised technical system searching is conducive to reduce exploration risk and promote success rate of hydrocarbon discovery. To illustrate the overall implementation procedure, a case study is applied and composed by 3 corresponding aspects: (1) based on well elastic parameters analysis, LamdaRho (Lame coefficient* Density) is inferred as the sensitive parameter of reservoir and hydrocarbon; (2) With the help of rock physic modeling and fluid substitution, we confirm that LMR is the most sensitive hydrocarbon parameter, and the LMR response varies from substituted fluid type;(3) Considering the difference of layer's buried-depth between evaluated structure and drilled wells, a buried depth correction is applied to eliminate its caused uncertainty of hydrocarbon predition.
The Effect of Pipe Rotation on Dynamic Well Control Surface Pressure Using Single Bubble Model
Authors: Al Marhoon Zahrah , Al Ramis Hussain 
Published: April 2019

Abstract
With the recent advances of drilling technology, carrying a safe well-constructed design is very important especially implementing the well control strategy. Managed Pressure Drilling (MPD) is a new technology that has recently emerged in the industry. It has special well control capabilities supported by the RCD to simultaneously provide the required pressure control on a certain volume gas influx and maintain the pipe rotation for drilling or any required operation. This paper examines the effect of pipe rotation on casing pressure profiles during the circulation process of the kick using MPD equipment.
Data from real scale kick experiments conducted by the LSU Petroleum Engineering Research & Technology Transfer Laboratory (PERTT Lab) personnel was analyzed. These experiments were conducted in a controlled environment that mimicked downhole conditions with a gas influx entering the wellbore. Then, the experimental analysis was coupled with the effect of pipe rotation through the application of correlations. The correlations from literature show a change in the expected frictional pressure loss when comparing the rotating case to the non-rotating case. The estimate in the change of frictional pressure loss in the annulus for non-Newtonian fluids with pipe rotation was done using two different correlations. This change is then applied on the geometric configuration of the well to find the change in the surface casing pressure caused by rotation.
This paper covers the use single bubble model in WBM. The model examined the change on the surface pressure caused by frictional pressure loss from pipe rotation.
The results from the models showed that the changes in pressure is very small with a percentage change up to 8 %. These changes are only applicable to cases with similar mud properties and well design of the experiments.
The practical outcome is to further the understanding of a gas bubble behavior in a wellbore experiencing a kick situation. Since new technologies allow for the rotation of the pipe during the circulation process, this paper helps in answering the question of whether or not the pipe rotation aids to overall expected surface pressure. Furthering the window of applicability of the MPD can possibly touch into its unexploited potential.
An Improved Model for Gas-Liquid Flow Pattern Prediction Based on Machine Learning
Authors: Mask Gene , Wu Xingru , Ling Kegang 
Published: April 2019

Abstract
Flow pattern of a multi-phase flow refers to the spatial distribution of the phase along transport conduit when liquid and gas flow simultaneously. The determination of flow patterns is a fundamental problem in two-phase flow analysis, and an accurate model for gas-liquid flow pattern prediction is critical for any multiphase flow characterization as the model is used in many applications in petroleum engineering. The objective of this study is to present a new model based on machine learning techniques and more than 8000 laboratory multi-phase flow tests.
The flow pattern is affected by fluid properties, in-situ flow rates of liquid and gas, and flow conduit geometry and mechanical properties. Laboratory data since 1950s have been collected and more than 8000 data points had been obtained. However, the actual flow conditions are significantly different with any laboratory settings. Therefore, several dimensionless variables are derived to characterize these data points first. Then machine learning techniques were applied on these dimensionless variables to develop the flow pattern prediction models. Applying hydraulic fundamentals and dimensional analysis, we developed dimensionless numbers to reduce number of freedom dimensions. These dimensionless variables are easy to use for upscaling and have physical meanings. We converted the collected data from actual laboratory measurement to the variations of these dimensionless variables. Machine learning techniques on the dimensionless variable significantly improved their predictive accuracy. Currently the best matching on these laboratory data was about 80% using the most recently developed semi-analytical models. Using machine learning techniques, we improved the matching quality to more than 90% on the experimental data.
This paper applies machine learning techniques on flow pattern prediction, which has tremendous practical usages and scientific merits. The developed model is better than current existing semi-analytical or classical correlations in matching the laboratory database.