CI Applications in the Oil and Gas Sector

Slide 1: CI Applications in the Oil and Gas Sector Ian D. Gates Chemical & Petroleum Engineering University of Calgary Marcel Bourque SGI Canada

Slide 2: Canada’s Place  Canada is One of the Few Countries that will be Raising Petroleum Production in the next 10 Years

Slide 3: 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

Slide 4: The Numbers  New Technologies Needed to Extract the Remaining Oil  Environmental Issues Key

Slide 5: Heavy Oil Becoming important source of energy and petroleum feed stock Typically, in situ Viscosity ~ 100,000 - 5,000,000 cP

Slide 6: 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 ?

Slide 7: 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)

Slide 8: Heavy Oil Growth Heavy Oil and Bitumen Production Becoming Increasingly More Important !

Slide 9: 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

Slide 10: 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

Slide 11: Reservoirs are Complex and Multiscale

Slide 12: Simplified Data Workflow

Slide 13: 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

Slide 14: 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

Slide 15: Reservoir Characterization & Visualization 3D Cave Environments (Courtesy Schlumberger) (Courtesy Windsprint)

Slide 16: Remote Team Collaboration (Courtesy Schlumberger)

Slide 17: Reservoir Simulation Geology; Properties of rocks; Models; Data Integration Reservoir Engineering, Process Design, Optimization, Multirealizations; Fluid Mechanics, Heat & Mass Transfer

Slide 18: 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).

Slide 19: 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

Slide 20: 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

Slide 21: Optimization: 100s to 1000s of Runs

Slide 22: Thermal-Solvent Recovery Process Design

Slide 23: 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

Slide 24: 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

Slide 25: 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