DOCSLIB.ORG

Identifying Reservoir Opportunities Using Automated Well Selection and Ranking

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Identifying Reservoir Opportunities Using Automated Well Selection and Ranking ® Originally appeared in World Oil OCTOBER 2020 issue, pgs 37-41. Posted with permission. RESERVOIR MANAGEMENT Identifying reservoir opportunities using automated well selection and ranking Effective reservoir The technology automates steps, typical- components, including: management requires ly performed during the selection of field • Engineering analytics - combining multiple development candidates, by applying ad- Automatically performs decline engineering/geoscience vanced algorithms and AI/ML to multi- curve analysis, using AI-based disciplines to identify disciplinary datasets, enabling teams to event detection and type rapidly review alternatives by leveraging curve generation; allocates improvement opportunities. cloud computing.1-3 This cloud-native production per zone for each To optimize analysis, an platform enables all members of an asset well, using a series of data- AI-powered management team to collaboratively assess field devel- driven techniques, integrating platform was developed that opment possibilities. production, completion, rock and delivers faster, more accurate It also integrates disparate sources fluid properties, and PLT/ILT results to maximize asset of data, including well logs, 3D reser- information. voir models, production history, and • Remaining pay identification - value. completion data, breaking down existing Identifies uncontacted pay with silos and opening new cross-functional many distinguishing features, workflows. Many steps are involved in such as pay connectivity analysis, ŝ HAMED DARABI, WASSIM BENHALLAM, generating a field development catalog, automatic baffle identification, JOHANNA SMITH, AMIR SALEHI and DAVID including identification of bypassed pay, perforation strategy and standoff CASTINEIRA, Quantum Reservoir Impact; drainage analysis, mapping of geo-en- constraints. EMMANUEL GRINGARTEN, Emerson gineering attributes to assess geological • Drainage analysis - Estimates Automation Solutions risks, and estimation of initial produc- areas that have been drained by tion potential. The process is an auto- existing wells, by offering both mated, systematic approach to assure a volumetric and facies-based reliable ranking of recompletion, infill drainage areas. Successful reservoir management re- and sidetrack options. • Wellbore accessibility - quires an up-to-date inventory of candi- Workflow automation allows asset Automatically evaluates the date opportunities that an engineering teams to run many more scenarios, ulti- mechanical feasibility via AI- team can pursue to meet expected pro- mately leading to better risk management based deciphering of wellbore duction targets. They include re-perfora- and shorter decision cycles. The synergy diagrams (automated wellbore tions, drilling a new well, or a sidetrack. that is formed between the domain ex- diagram digitization and feasibility Finding the best solutions requires com- perts and AI during the process ensures classification). bining geological knowledge, reservoir that the selected candidates are aligned • Geological risk assessment - behavior, production history, comple- with overall reservoir management strat- Automatically assesses structural tion information, and multi-disciplinary egy and that they satisfy pertinent engi- and mapping risks. know-how. The conventional process of neering and economic constraints. • Production rate forecast - gathering, vetting and analyzing data is Estimates production gains by labor-intensive and generally takes sev- METHODOLOGY selecting from many available eral months. It requires the use of mul- The framework consists of several options containing statistical, tiple software applications, making col- laboration difficult and often leading to an unreliable set of candidates. Also, it is Fig. 1. Summary of recompletion finder workflow. complicated to look at multiple scenari- os under different hypotheses and leaves little time to rigorously vet options un- der review. SpeedWise Reservoir Opportunity (SRO) is an AI-based technology, the re- sult of a collaboration between Emerson and Quantum Reservoir Impact (QRI). World Oil® / OCTOBER 2020 37 RESERVOIR MANAGEMENT available to accelerate the vetting pro- Fig. 2. An example dashboard displaying summary of identified opportunities, location map, distribution by production zone and ranking based on production gain. cess and promote collaboration between asset team members. An example dash- board highlighting selected options, lo- cation map, distribution by production zone and ranking based on production gains is shown in Fig. 2. CASE STUDIES The technology has been applied suc- cessfully to a diverse portfolio of over 100 onshore and offshore oil and gas fields producing from carbonates and sandstones as primary production and waterflooding. Significant value has been generated in these fields by increasing production, reserves, and capital efficacy while enabling more robust decision- making and increasing organizational agility. Four case studies are highlighted below as a reference. Table 1 exhibits or- ders of magnitude of efficiency attained for these case examples in terms of time, person-months spent, and the number of scenarios explored. Case study 1 - Latin American sand- stone. The asset is a mature field with over 70 years of production history from 200 wells (mainly vertical well develop- ment). After a long period of primary analytical and ML-based models. engineering properties; what should be production, waterflooding has started • Target search - Identifies optimal minimum/maximum spacing between over the last ten years. The reservoir is locations for placing target wells, the wells; what are the cut-offs for net a tertiary fluvio-deltaic to alluvial silici- using robust and fast optimization pay estimation; and how to define the clastic in a faulted anticlinal trap, with techniques, featuring relative probability of success parameters. By an- low resistivity pay and 18 distinct layers. probability of success mapping and alyzing historical field performance and There was a need to identify recomple- comprehensive geo-engineering benchmarking against analog assets, the tion and infill drilling candidates that are constraints. technology intelligently picks the best aligned with overall reservoir manage- These individual components are as- settings, tailored to address the unique ment strategy, satisfy both geological and sembled to build larger distinct work- challenges posed by the field. engineering constraints, provide reliable flows, namely recompletion finder, ver- The assumptions and settings can be forecasts and are mechanically viable. tical sweet spots, and horizontal target altered to create many more scenarios The asset team’s existing workflow to up- search. Figure 1 illustrates the workflow effortlessly and account for uncertain- date the inventory was deterministic and for the recompletion finder, as many of ties in the key parameters. After the job would take over six months. One of the the mentioned elements are connected. is executed in a scalable and secure cloud key challenges was the poor understand- After uploading the required multi- environment, typically in a matter of ing of reservoir compartmentalization disciplinary data for a field, it usually minutes, the results are accessible via a and delineation of both original and cur- takes only a few minutes/hours to gener- set of interactive browser-based dash- rent remaining oil. This jeopardized the ate a catalog of field development candi- boards, ready for the asset team’s review reliability of the results generated by the dates. First, the dataset is automatically and vetting. Multiple views integrating existing deterministic workflow. QCed and validated by leveraging AI- multi-disciplinary data and analysis are The opportunity identification based techniques. Once the integrity of presented. framework presented was leveraged by the data is verified, the user is ready to These include an executive summary, the asset team, aiming to increase the experiment. Typically, several decisions historical well card and individual op- speed and accuracy of results. Fifteen need to be made for each experiment, portunity cards summarizing the criti- scenarios (three different geomodels controlled through more than 200 set- cal information related to each prospect. with five distinct setting groups varying tings that provide ultimate flexibility Additionally, petrophysical characteriza- most influential uncertain parameters) and customization. For example, which tion, geo-model assessment, production were generated to achieve a range of method to use for mapping the geo- forecast, and mechanical feasibility are potential outcomes and account for the 38 OCTOBER 2020 / WorldOil.com RESERVOIR MANAGEMENT uncertainty in crucial parameters. Af- powered solution to overcome the ex- over 50 years of production history and ter screening and evaluating more than isting obstacles and detect any remain- 90 active producers (mainly vertical well 10,000 recompletion and 17,000 vertical ing behind-pipe potential that could be development), under an active water- well possibilities, dozens of recomple- tapped into by recompleting existing flood. Previous reservoir management tions/reactivations (with potential oil wells. More than 30 scenarios were gen- and recent drilling strategy resulted in a gains between 4,600 to 7,000 bopd) and erated to account for uncertainty in sev- rapid decline in oil production over the vertical wells (with potential oil gains eral key parameters.
Load more

Recommended publications
  • The Open Petroleum Engineering Journal
    1874-8341/19 Send Orders for Reprints to [email protected] 1 The Open Petroleum Engineering Journal Content list available at: https://openpetroleumengineeringjournal.com RESEARCH ARTICLE Analysis of Spatial Distribution Pattern of Reservoir Petrophysical Properties for Horizontal Well Performance Evaluation-A Case Study of Reservoir X Aidoo Borsah Abraham1,*, Annan Boah Evans1 and Brantson Eric Thompson2 1Oil and Gas Engineering Department, School of Engineering, All Nations University College, Koforidua, Ghana 2Petroleum Engineering Department, Faculty of Mineral Resources Technology, University of Mines and Technology, Tarkwa, Ghana Abstract: Introduction: Building a large number of static models to analyze reservoir performance is vital in reservoir development planning. For the purpose of maximizing oil recovery, reservoir behavior must be modelled properly to predict its performance. This requires the study of the variation of the reservoir petrophysical properties as a function of spatial location. Methods: In recent times, the method used to analyze reservoir behavior is the use of reservoir simulation. Hence, this study seeks to analyze the spatial distribution pattern of reservoir petrophysical properties such as porosity, permeability, thickness, saturation and ascertain its effect on cumulative oil production. Geostatistical techniques were used to distribute the petrophysical properties in building a 2D static model of the reservoir and construction of dynamic model to analyze reservoir performance. Vertical to horizontal permeability anisotropy ratio affects horizontal wells drilled in the 2D static reservoir. The performance of the horizontal wells appeared to be increasing steadily as kv/kh increases. At kv/kh value of 0.55, a higher cumulative oil production was observed compared to a kv/kh ratio of 0.4, 0.2, and 0.1.
    [Show full text]
  • Statoil ASA Statoil Petroleum AS
    Offering Circular A9.4.1.1 Statoil ASA (incorporated with limited liability in the Kingdom of Norway) Notes issued under the programme may be unconditionally and irrevocably guaranteed by Statoil Petroleum AS (incorporated with limited liability in the Kingdom of Norway) €20,000,000,000 Euro Medium Term Note Programme On 21 March 1997, Statoil ASA (the Issuer) entered into a Euro Medium Term Note Programme (the Programme) and issued an Offering Circular on that date describing the Programme. The Programme has been subsequently amended and updated. This Offering Circular supersedes any previous dated offering circulars. Any Notes (as defined below) issued under the Programme on or after the date of this Offering Circular are issued subject to the provisions described herein. This does not affect any Notes issued prior to the date hereof. Under this Programme, Statoil ASA may from time to time issue notes (the Notes) denominated in any currency agreed between the Issuer and the relevant Dealer (as defined below). The Notes may be issued in bearer form or in uncertificated book entry form (VPS Notes) settled through the Norwegian Central Securities Depositary, Verdipapirsentralen ASA (the VPS). The maximum aggregate nominal amount of all Notes from time to time outstanding will not exceed €20,000,000,000 (or its equivalent in other currencies calculated as described herein). The payments of all amounts due in respect of the Notes issued by the Issuer may be unconditionally and irrevocably guaranteed by Statoil A6.1 Petroleum AS (the Guarantor). The Notes may be issued on a continuing basis to one or more of the Dealers specified on page 6 and any additional Dealer appointed under the Programme from time to time, which appointment may be for a specific issue or on an ongoing basis (each a Dealer and together the Dealers).
    [Show full text]
  • Reservoir Simulation
    Reservoir Simulation NETHERLAND, SEWELL & ASSOCIATES, INC. One of the most respected names in global petroleum consulting Preferred by companies who need reliable results Quality at a competitive price Expertise in Reservoir Simulation Numerical reservoir simulation is a state-of-the- art evaluation tool that includes material balance, fluid flow, reservoir heterogeneity, well interference, wellbore hydraulics, and facility characteristics in its predictions of reservoir performance. Simulation can be a valuable tool to determine the best development plan for a new reservoir or to improve an existing field by understanding historical production behavior. Experience has taught us that in order for reservoir simulation to be a useful evaluation tool, it must be implemented by an experienced, multi-functional team of geoscientists and reservoir engineers. The Reservoir Simulation team at Netherland, Sewell & Associates, Inc. (NSAI) is comprised of experts who have been working with simulation tools for over 15 years and have been evaluating reservoirs around the world for over 20 years. Reservoir Simulation Experts Dave Adams - Reservoir/Simulation Engineer - Dallas Mike Begland - Reservoir/Simulation Engineer - Dallas Chris Tucker - Reservoir/Simulation Engineer - Dallas Derek Newton - Reservoir/Simulation Engineer - Houston Methodology We use black oil and compositional models in our studies, and our experts are proficient with a variety of simulation software applications including Schlumberger Eclipse® and Halliburton Landmark’s VIP®. No job is too large—our history match models have included fields with over 1,200 wells and 80 years of history. Be it a single-well evaluation, a mechanistic model, or a full-field history match, our experts are skilled in all aspects of reservoir simulation.
    [Show full text]
  • Deep Borehole Placement of Radioactive Wastes a Feasibility Study
    DEEP BOREHOLE PLACEMENT OF RADIOACTIVE WASTES A FEASIBILITY STUDY Bernt S. Aadnøy & Maurice B. Dusseault Executive Summary Deep Borehole Placement (DBP) of modest amounts of high-level radioactive wastes from a research reactor is a viable option for Norway. The proposed approach is an array of large- diameter (600-750 mm) boreholes drilled at a slight inclination, 10° from vertical and outward from a central surface working site, to space 400-600 mm diameter waste canisters far apart to avoid any interactions such as significant thermal impacts on the rock mass. We believe a depth of 1 km, with waste canisters limited to the bottom 200-300 m, will provide adequate security and isolation indefinitely, provided the site is fully qualified and meets a set of geological and social criteria that will be more clearly defined during planning. The DBP design is flexible and modular: holes can be deeper, more or less widely spaced, at lesser inclinations, and so on. This modularity and flexibility allow the principles of Adaptive Management to be used throughout the site selection, development, and isolation process to achieve the desired goals. A DBP repository will be in a highly competent, low-porosity and low-permeability rock mass such as a granitoid body (crystalline rock), a dense non-reactive shale (chloritic or illitic), or a tight sandstone. The rock matrix should be close to impermeable, and the natural fractures and bedding planes tight and widely spaced. For boreholes, we recommend avoiding any substance of questionable long-term geochemical stability; hence, we recommend that surface casings (to 200 m) be reinforced polymer rather than steel, and that the casing is sustained in the rock mass with an agent other than standard cement.
    [Show full text]
  • RESERVOIR ENGINEERING for Geologists
    RESERVOIR ENGINEERING for Geologists PRINCIPAL AUTHORS Ray Mireault, P. Eng. Lisa Dean, P. Geol. CONTRIBUTING AUTHORS Nick Esho, P. Geol. Chris Kupchenko, E.I.T. Louis Mattar, P. Eng. Gary Metcalfe, P. Eng. Kamal Morad, P. Eng. Mehran Pooladi-Darvish, P. Eng. cspg.org fekete.com Reservoir Engineering for Geologists was originally published as a fourteen-part series in the CSPG Reservoir magazine between October 2007 and December 2008. TABLE OF CONTENTS Overview...................................................................................... 03 COGEH Reserve Classifications.................................................. 07 Volumetric Estimation ..................................................................11 Production Decline Analysis.........................................................15 Material Balance Analysis.............................................................19 Material Balance for Oil Reservoirs.............................................. 23 Well Test Interpretation................................................................. 26 Rate Transient Analysis................................................................ 30 Monte Carlo Simulation/Risk Assessment - Part 1...................... 34 Monte Carlo Simulation/Risk Assessment - Part 2...................... 37 Monte Carlo Simulation/Risk Assessment - Part 3 ...................... 41 Coalbed Methane Fundamentals................................................ 46 Geological Storage of CO2........................................................... 50
    [Show full text]
  • Petroleum Engineering (PETE) | 1
    Petroleum Engineering (PETE) | 1 PETE 3307 Reservoir Engineering I PETROLEUM ENGINEERING Fundamental properties of reservoir formations and fluids including reservoir volumetric, reservoir statics and dynamics. Analysis of Darcy's (PETE) law and the mechanics of single and multiphase fluid flow through reservoir rock, capillary phenomena, material balance, and reservoir drive PETE 3101 Drilling Engineering I Lab mechanisms. Preparation, testing and control of rotary drilling fluid systems. API Prerequisites: PETE 3310 and PETE 3311 recommended diagnostic testing of drilling fluids for measuring the PETE 3310 Res Rock & Fluid Properties physical properties of drilling fluids, cements and additives. A laboratory Introduction to basic reservoir rock and fluid properties and the study of the functions and applications of drilling and well completion interaction between rocks and fluids in a reservoir. The course is divided fluids. Learning the rig floor simulator for drilling operations that virtually into three sections: rock properties, rock and fluid properties (interaction resembles the drilling and well control exercises. between rock and fluids), and fluid properties. The rock properties Corequisites: PETE 3301 introduce the concepts of, Lithology of Reservoirs, Porosity and PETE 3110 Res Rock & Fluid Propert Lab Permeability of Rocks, Darcy's Law, and Distribution of Rock Properties. Experimental study of oil reservoir rocks and fluids and their interrelation While the Rock and Fluid Properties Section covers the concepts of, applied
    [Show full text]
  • ECLIPSE 2012 Reservoir Simulation Software Industry-Reference Simulator
    ECLIPSE 2012 Reservoir Simulation Software Industry-reference simulator ECLIPSE* reservoir simulation software provides a complete and robust upscaling, history match analysis, uncertainty and sensitivity analysis, set of numerical solutions for fast and accurate prediction of dynamic well path and completion design, and design optimization of well behavior—for all types of reservoirs and degrees of complexity, including locations, completions, and reservoir recovery methods. structure, geology, fluids, and development schemes. Blackoil simulation The ECLIPSE industry-reference simulator covers the entire spectrum The ECLIPSE Blackoil simulator supports three-phase, 3D reservoir of reservoir simulation, including black-oil, compositional, and thermal simulation with extensive well controls, field operations planning, and finite-volume reservoir simulation, as well as ECLIPSE FrontSim comprehensive enhanced oil recovery (EOR) schemes. streamline reservoir simulation capabilities. With a wide range of add-on options—such as coal and shale gas, enhanced oil recovery, advanced Compositional simulation wells, and surface networks—you can tailor the simulator capabilities, When modeling multicomponent hydrocarbon flow, the ECLIPSE enhancing the scope of your reservoir simulation studies. Compositional simulator provides a detailed description of reservoir fluid phase behavior and compositional changes. With their depth and breadth of capabilities, innovative technologies, robustness, speed, parallel scalability, and platform coverage, ECLIPSE
    [Show full text]
  • Reservoir Simulation for Strategic Decisions Simulation for Strategically Sound Economic Decisions
    Reservoir Simulation for Strategic Decisions Simulation for Strategically Sound Economic Decisions E&P companies are increasingly making better investment decisions for costs can run into the millions of dollars, Ryder Scott reservoir models field development by using reservoir simulation. These built-for-purpose models pay for themselves again and again. help you devise development or operational strategies to maximize recovery and profit. Your objective may be to develop behind-pipe reserves, identify infill- Clients using Ryder Scott reservoir models avoid drilling opportunities, optimize a pressure maintenance program or determine over-development and over-drilling. They put efficient well spacing. Or you may have other goals, such as evaluating their projects on the fast track, capture changes to processing facilities or improving gas-storage operations. What- more reserves per well, increase ever the case, reviewing model runs leads to better decisions by helping predict field efficiency, boost ultimate complex reservoir behavior and field performance under various drilling and recoveries and improve operating scenarios. overall economics. Typically, a simulation study guides and, in some cases, limits development activities that cost far more than the simulation itself. Since drilling and completion Reviewing model runs leads to better decisions by helping predict complex reservoir behavior and field performance. The Utility of the Simulation Tool A reservoir simulation model is a tool that helps E&P companies make informed business decisions regarding oil and gas reserves estimates, reservoir management, reservoir performance, process design and strategic planning. Nearly every type of field-production scenario can be modeled. Ryder Scott constructs and executes models to predict the performance of straight, horizontal and directional wells, well patterns, sectors of fields, entire fields and wellbore tubulars linked to the surface.
    [Show full text]
  • New Petrophysical Magnetic Methods MACC and MAFM in Permeability
    Geophysical Research Abstracts Vol. 14, EGU2012-13161, 2012 EGU General Assembly 2012 © Author(s) 2012 New petrophysical magnetic methods MACC and MAFM in permeability characterisation of petroleum reservoir rock cleaning, flooding modelling and determination of fines migration in formation damage O. P. Ivakhnenko Department of Petroleum Engineering, Kazakh-British Technical University, 59 Tolebi Str. Almaty, Kazakhstan ([email protected]; [email protected]/Fax: +7 727 2720487) Potential applications of magnetic techniques and methods in petroleum engineering and petrophysics (Ivakhnenko, 1999, 2006; Ivakhnenko & Potter, 2004) reveal their vast advantages for the petroleum reser- voir characterisation and formation evaluation. In this work author proposes for the first time developed systematic methods of the Magnetic Analysis of Core Cleaning (MACC) and Magnetic Analysis of Fines Migration (MAFM) for characterisation of reservoir core cleaning and modelling estimations of fines migration for the petroleum reservoir formations. Using example of the one oil field we demonstrate results in application of these methods on the reservoir samples. Petroleum reservoir cores samples have been collected within reservoir using routine technique of reservoir sampling and preservation for PVT analysis. Immediately before the MACC and MAFM studies samples have been exposed to atmospheric air for a few days. The selected samples have been in detailed way characterised after fluid cleaning and core flooding by their mineralogical compositions and petrophysical parameters. Mineralogical composition has been estimated utilizing XRD techniques. The petrophysical parameters, such as permeability and porosity have been measured on the basis of total core analysis. The results demonstrate effectiveness and importance of the MACC and MAFM methods for the routine core analysis (RCAL) and the special core analysis (SCAL) in the reservoir characterisation, core flooding and formation damage analysis.
    [Show full text]
  • Applied Earth Sciences Natural Resources from the Earth, Ranging from Engineers Know Where Those Resources Can Be Found Raw Materials to Energy
    complement your academic studies, you will have the opportunity to work intensively with TU Delft’s partners in industry. For example, TU Delft is a participant in ISAPP (Integrated System Approach Petroleum Production), a large collaborative project involving TU Delft, Shell and TNO established for the purpose of boosting oil production by improving the flow of oil and water in oil reservoirs, and CATO, a consortium doing research on the collection, transport and storage of CO2. Managing the Earth’s resources for today and tomorrow Programme tracks • Petroleum Engineering and Geosciences covers both the technologies involved in extracting petroleum from the Earth, and the tools for assessing hydrocarbon reservoirs to gain an MSc Programme understanding of their potential. The track is divided into two specialisations: Petroleum Engineering covers all upstream Applied Earth aspects from reservoir description and drilling techniques to field management and project Sciences economics. Reservoir Geology covers the use of modern measurement and computational methods to obtain a quantitative understanding of hydrocarbon reservoirs. • Applied Geophysics is a joint degree track offered collaboratively by TU Delft, ETH Zürich and RWTH Aachen University. It trains students in geophysical aspects of environmental and engineering studies and in the exploration, exploitation and management of hydrocarbon and geothermal energy. Disciplines covered include acoustic and electromagnetic wave theory, seismic data acquisition, imaging and interpretation, borehole logging, rock-fluid interaction and petroleum geology. Everything we build and use on the surface of our • Resource Engineering covers the extraction of planet comes from the Earth. Applied Earth Sciences natural resources from the Earth, ranging from engineers know where those resources can be found raw materials to energy.
    [Show full text]
  • Best Research Support and Anti-Plagiarism Services and Training
    CleanScript Group – best research support and anti-plagiarism services and training List of oil field acronyms The oil and gas industry uses many jargons, acronyms and abbreviations. Obviously, this list is not anywhere near exhaustive or definitive, but this should be the most comprehensive list anywhere. Mostly coming from user contributions, it is contextual and is meant for indicative purposes only. It should not be relied upon for anything but general information. # 2D - Two dimensional (geophysics) 2P - Proved and Probable Reserves 3C - Three components seismic acquisition (x,y and z) 3D - Three dimensional (geophysics) 3DATW - 3 Dimension All The Way 3P - Proved, Probable and Possible Reserves 4D - Multiple Three dimensional's overlapping each other (geophysics) 7P - Prior Preparation and Precaution Prevents Piss Poor Performance, also Prior Proper Planning Prevents Piss Poor Performance A A&D - Acquisition & Divestment AADE - American Association of Drilling Engineers [1] AAPG - American Association of Petroleum Geologists[2] AAODC - American Association of Oilwell Drilling Contractors (obsolete; superseded by IADC) AAR - After Action Review (What went right/wrong, dif next time) AAV - Annulus Access Valve ABAN - Abandonment, (also as AB) ABCM - Activity Based Costing Model AbEx - Abandonment Expense ACHE - Air Cooled Heat Exchanger ACOU - Acoustic ACQ - Annual Contract Quantity (in reference to gas sales) ACQU - Acquisition Log ACV - Approved/Authorized Contract Value AD - Assistant Driller ADE - Asphaltene
    [Show full text]
  • Elasto-Plastic Deformation and Flow Analysis in Oil
    ELASTO-PLASTIC DEFORMATION AND FLOW ANALYSIS IN OIL SAND MASSES by THILLAIKANAGASABAI SRITHAR B. Sc (Engineering), University of Peradeniya, Sri Lanka, 1985 M. A. Sc. (Civil Engineering) University of British Columbia, 1989 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES Department of CIVIL ENGINEERING We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA April, 1994 © THILLAIKANAGASABAI SRITHAR, 1994 _______________________ In . presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. (Signature) Department of Civil Engineering The University of British Columbia Vancouver, Canada Date - A?R L 9 L DE-6 (2188) Abstract Prediction of stresses, deformations and fluid flow in oil sand layers are important in the design of an oil recovery process. In this study, an analytical formulation is developed to predict these responses, and implemented in both 2-dimensional and 3-dimensional finite element programs. Modelling of the deformation behaviour of the oil sand skeleton and modelling of the three-phase pore fluid behaviour are the key issues in developing the analytical procedure. The dilative nature of the dense oil sand matrix, stress paths that involve decrease in mean normal stress under constant shear stress, and loading-unloading sequences are some of the important aspects to be considered in modelling the stress-strain behaviour of the sand skeleton.
    [Show full text]