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CI Applications in the Oil and Gas Sector

CI Applications in the Oil and Gas Sector



Ian Gates's presentation from Cybera's 2007 Banff Cyberinfrastructure Summit

Ian Gates's presentation from Cybera's 2007 Banff Cyberinfrastructure Summit



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    CI Applications in the Oil and Gas Sector CI Applications in the Oil and Gas Sector Presentation Transcript

    • CI Applications in the Oil and Gas Sector Ian D. Gates Chemical & Petroleum Engineering University of Calgary Marcel Bourque SGI Canada
    • Canada’s Place  Canada is One of the Few Countries that will be Raising Petroleum Production in the next 10 Years
    • Recovery Technology is the Key  Conventional Oil Harder to Find and Require More Intensive Recovery Processes for Production  Heavy Oil becoming Major Source for Petroleum Energy  Unconventional Gas e.g. CBM, Tight Gas becoming Major Source for Gas  What was Once Inaccessible Petroleum is Now becoming a Target for Production
    • The Numbers  New Technologies Needed to Extract the Remaining Oil  Environmental Issues Key
    • Heavy Oil Becoming important source of energy and petroleum feed stock Typically, in situ Viscosity ~ 100,000 - 5,000,000 cP
    • Heavy Oil Growth Roughly 10 Trillion Barrels of Heavy Oil Resource This is about 3x that of Conventional Oil Resource In Alberta, have about 2 Trillion Barrels Heavy Oil Key Question: What is the best technology available to recover this resource ? How much of this resource is recoverable ?
    • Heavy Oil Recovery Typically, in Alberta, Recovery Factor for Heavy Oil is between 10 and 50% depending on Recovery Technology For the future, need to consider what is currently considered Inaccessible Reservoirs: Bitumen from Carbonates Bitumen from Thin Pay (< 15 m)
    • Heavy Oil Growth Heavy Oil and Bitumen Production Becoming Increasingly More Important !
    • Heavy Oil Growth in Alberta Alberta In-Situ Bitumen Production Source: AEUB ST-53 500 450 400 350 Bitumen (kBPD) 300 250 200 150 100 50 0 1998 1999 2000 2001 2002 2003 2004 2005 CSS SAGD Cold Flow HWs Waterflood
    • Heavy Oil Growth in Alberta → Cold Lake Bitumen 11 API; 1-300,000 cP Peace River Bitumen 9-10 API; 200,000 cP Athabasca Bitumen 8-9 API; 2-5 Million cP → 1996-2002, oil sands industry spent over $19 Billion on new projects → ~$100 Billion may be spent on new projects in the 2003-2020 period → Large water, natural gas, & diluent requirements
    • Reservoirs are Complex and Multiscale
    • Simplified Data Workflow
    • Business Drivers for HPC in Oil & Gas  Need to Improve Efficiency & Automate Tasks; Shorter Execution Times  Use More Complex Reservoir Models & Physics; More Analysis Needed; More Simulations Done  Have Less Easy Oil; Nonconventional Sources; Exploration More Expensive and Difficult than Ever  Need to Maximize Productivity from Existing Assets  Data Acquisition Larger than Ever  HURDLE: OIL & GAS OFTEN NOT EARLY ADOPTERS
    • HPC Computing in Oil & Gas  Data Integration from Multiple Sources; Superlarge Datasets  Geological Modelling & Visualization  Reservoir Modelling, Simulation, Post- Processing, & Visualization  Recovery Process Design & Optimization  Risk Management & Uncertainty Analysis  Seismic Processing  Remote Teamwork & Communication  ENABLES DECISION MAKING
    • Reservoir Characterization & Visualization 3D Cave Environments (Courtesy Schlumberger) (Courtesy Windsprint)
    • Remote Team Collaboration (Courtesy Schlumberger)
    • Reservoir Simulation Geology; Properties of rocks; Models; Data Integration Reservoir Engineering, Process Design, Optimization, Multirealizations; Fluid Mechanics, Heat & Mass Transfer
    • Physics in Reservoir Simulators  Capabilities: 1. Darcy and non-Darcy flow, 2. heat transfer (heat losses to overburden understrata; conduction; convection; in situ heat generation; impact of temperature on fluid properties, reactions, rock- fluid and other properties), 3. mass transfer (reactant and product diffusion, dispersion, and convection), 4. chemical and geochemical reactions (in situ upgrading; biodegradation and bioreactions; reactions of injectants with reservoir rock; definition of reactions and components; reaction order and rate constants and other associated parameters), 5. phase behaviour (PVT properties and representation in reservoir simulator; breakdown of heavy oil and bitumen into pseudocomponents; biodegradation phase behaviour), 6. formation impacts (plugging of formation by heavier reaction products; flow of catalyst in formation and solids transport), 7. geomechanics (thermal expansion and thermally-induced shear; dilation; fracture formation and propagation; wormhole formation), 8. geophysics (rock physics; synthetic seismograms), and 9. wellbore flow (multiphase flow in undulating wellbores; design of wellbore trajectory).
    • Simulation Implementation Issues • Part one of the problem – due to amount of data and size of problem, multiscale simulations take lots of time • Part two of the problem – usually one simulation run is not sufficient – need to run several to many hundreds and thousands to choose the right course of action • Part three of the problem – existing software does not make full use of new software/hardware technologies that address the above issues
    • Simulation Implementation Issues • Large amounts of data, huge simulations, multiple iterations, not an isolated single run • Computing community has responded with standardized Parallel Computing • Industry have also responded by developing dedicated Hardware Co-simulators • The two points above produce speed increases of orders of magnitude • Programming languages, compilers, processor types do not
    • Optimization: 100s to 1000s of Runs
    • Thermal-Solvent Recovery Process Design
    • Resistance to Early Adoption of Grid/HPC  Culture and Adversity to Risk; Tape Storage  Proprietary Data & Security; Competitive Advantage  Network Data Transfer Capability, Security, & Storage Needs to be Expanded  Unclear Benefits; Few Proven Cost / Benefit  Lots of Legacy Code; Few Applications Capable of Full Utilization of Grid/HPC  Network Capabilities / Costs to Link Clusters  People and Skills; User Education
    • Where is Oil & Gas Now?  Overall Limited Linked grids and Use of HPC  Single Applications that Often Do Not Scale beyond about 4 to 8 Processors  Main Applications: Seismic, Reservoir Modeling  Running into Data Management Constraints  Yet More Interest in Benefits of Grid/HPC  Note: Seismic Processing quite Mature
    • Major Growth for the Future  Main Growth in Reservoir Simulation with Move towards Design Optimization, Risk and Uncertainty Assessment  Growth in Data Transfer, Storage, & Management with Security as Major Concern  Remote Collaboration