INSTRUCTOR © 2017, John R. Fanchi All rights reserved. No part of this manual may be reproduced in any form without the express written permission of the author. © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

To the Instructor The set of files here are designed to help you prepare lectures for your own course using the text Introduction to Petroleum Engineering, J.R. Fanchi and R.L. Christiansen (Wiley, 2017) File format is kept simple so that you can customize the files with relative ease using your own style. You will need to supplement the files to complete the presentation topics.

RESERVOIR PERFORMANCE © 2017, John R. Fanchi All rights reserved. No part of this manual may be reproduced in any form without the express written permission of the author. © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Outline Reservoir Flow Simulators Reservoir Flow Modeling Workflows Performance of Conventional Oil and Gas Reservoirs Performance of an Unconventional Reservoir Performance of Geothermal Reservoirs Homework: IPE Ch. 14

RESERVOIR FLOW SIMULATORS © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Flow Model Reservoir Simulation Subsystems Surface Model Wellbore Model Well Model Reservoir Model

Reservoir Subdivisions Subdivide reservoir into subregions Require for each subregion: mass entering – mass leaving = mass accumulation Volume Element Unconformity

What is a flow unit*? “a volume of rock subdivided according to geological and petrophysical properties that influence the flow of fluids through it.” * W.J. Ebanks, Jr., 1987 AAPG Annual Meeting

What is a flow unit*? A mappable portion of the total reservoir within which geological and petrophysical properties that affect the flow of fluids are consistent and predictably different from the properties of other reservoir rock volumes (after Ebanks, 1987) * Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

Characteristics of a flow unit* A specific volume of reservoir composed of One or more reservoir quality lithologies Any nonreservoir quality rock types Fluids they contain Correlative and mappable at the interwell scale Flow unit zonation is recognizable on wireline logs May be in communication with other flow units * Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

Flow Units and Geostatistics Flow units are “mostly deterministic” Use geostatistics conditioned by well data To distribute petrophysical properties To create stochastic realizations * Ebanks, Scheihing and Atkinson (1993): AAPG Methods #10

Extended Black Oil Simulator Flow Equations Stock Tank Oil Water plus Surfactant Surfacant Soluble Species © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Discretize time into time steps Finite Differences Formulate fluid flow equations, e.g. Approximate derivatives with finite differences Discretize region into grid blocks Discretize time into time steps Numerically solve set of linear algebraic equations

Finite Difference Representation Production Wells Injection Wells Distributions S = S(x,y,z,t) P = P(x,y,z,t) Spatial Discretization Time Discretization Aspect Ratio of Block Width / length Eg. y / x for areal grid No Flow Nodes

Digitize Mapped Properties

Numerical Dispersion Arises from time and space discretizations Leads to smeared spatial gradients saturation, concentrations Depends on grid-block size and time-step size

Well Models Vertical Deviated Horizontal Multilateral

RESERVOIR FLOW MODELING WORKFLOWS © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Traditional Brown Field Flow Modeling Workflow Illustrative Deterministic History Matching Workflow (after Williams, et al., 1998)

Green Fields and Brown Fields Data requirements depend on field history Green Field Essentially an undeveloped field Minimal production – injection history Brown Field Essentially a developed field Significant production – injection history

Green Field Flow Modeling Workflow Step Task G1 Gather Data G2 Identify Key Parameters and Associated Uncertainties G3 Generate Forecast of Field Performance Results G4 Generate Distribution of Field Performance Results (Proxies facilitate statistical analysis)

Green Field Flow Modeling Workflow (minimal history) Identify parameters and uncertainties Gather data Generate recovery distribution Generate prod-inj forecasts

How many trial runs should be made? Experimental Design Different ways to design experiment Full factorial design Select p input parameters Vary each parameter using q values 3-Level Design uses q = 3 values e.g. Min, Most Likely, Max # of trial runs = pq 3-Level Full factorial design example Let p = 3 and q = 3 # of trial runs = pq = 33 = 27

Illustrate q-Level Design Parameter Space Select p = 3 input parameters (x1, x2, x3) 2-Level Design uses q = 2 values e.g. Min, Max 3-Level Design uses q = 3 values e.g. Min, Most Likely, Max fills in parameter space # of runs = 3q

Modern Brown Field Flow Modeling Workflow Step Task B1 Gather Data B2 Identify Input Parameters and Associated Uncertainties B3 Identify History Match Constraints and History Match Variables B4 Generate Forecast of Field Performance Results B5 Determine Quality of History Match (Select subset of acceptable HM cases) B6 Generate Distribution of Field Performance Results (Proxies facilitate statistical analysis) B7 Verify Workflow

Brown Field Flow Modeling Workflow Identify input parameters and uncertainties Brown field (prod-inj history) Gather data Identify HM variables and constraints Generate prod-inj forecasts Variable Constraints Pressure < 10% Oil Rate < 2% Water Rate Verify Workflow Recovery Results from Subset Determine Quality of HM (Select Subset)

PERFORMANCE OF CONVENTIONAL OIL AND GAS RESERVOIRS © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Wilmington Field, California Immiscible Displacement by Water Flooding

Wilmington Field Fault Blocks and Stratigraphic Zones

Prudhoe Bay Field, Alaska Water Flood, Gas Cycling, and Miscible Gas Injection

Schematic Cross-Section of Prudhoe Bay Field, Alaska

PERFORMANCE OF AN UNCONVENTIONAL RESERVOIR © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Barnett Shale, Texas Shale Gas Production

Barnett Shale, Texas Development Area

Barnett Shale, Texas Drilling Rig

Wellbore Trajectories Drilled from a Shale Development Well Pad

Surface Equipment at a Shale Gas Well Pad

Water Disposal Wells TX Railroad Commission must approve sites Barnett Shale at 5000 to 7000 ft Dispose in Ellenburger LS at 10,000 to 12,000 feet

Environmental Impact: Earthquakes Several earthquakes in 2009 < 2.0 to 3.0 Richter quakes Barnett is 5,000-7000’ deep Two disposal wells near quakes Disposal wells are 10-12,000’ deep Known faults in area Faults originate >14,000’ deep Tremors are from 14,000-15,000 ft UT and SMU seismograph study No direct relationship proven

Working with Communities ANSI – API Bulletin 100-3: Community Engagement Consequence of unconventional resource development Prepare communities for exploration activities Minimize disruption to communities Manage resources Source: J. Donnelly, “Community Engagement,” JPT, Sep. 14, pg. 18

Summary Barnett Shale A pioneer in unconventional shale drilling and production techniques Deviated drilling Hydraulic fracturing Will continue to guide other unconventional shale plays in the United States and around the world. Areas for improvement: Extend field/well production life Improve accuracy of reserve estimates Develop improved recovery techniques

PERFORMANCE OF GEOTHERMAL RESERVOIRS © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

Puna Geothermal Venture (PGV), Hawaii

Communities and Well Locations ca. 2005 PGV = Puna Geothermal Venture [formerly HGPA operation]

HGPA Geothermal Operations Initial operator: State of Hawaii HGPA: Hawaii Geothermal Project – Well A Experimental Geothermal Station Operated from 1981-89 Power: 2.2 MW

Puna Geothermal Operations Puna Geothermal Venture (PGV) Commenced operation in 1993 Power: 38 MW (30 MW + 8 MW expansion) PGV acquired by Ormat in June 2004 Customer: Hawaii Electric Light Output Contract to deliver 25 – 30 MW continuously ~ 20% of Big Island consumption Puna 8 MW Expansion Source: http://www.ormat.com/case-studies/puna-geothermal-venture-hawaii, accessed 2-28-14

2 air-cooled power plants: Closed cycle and Binary system Puna Geothermal Power Flash-Binary Power Plant Well ~ 1 mi deep Well 2 air-cooled power plants: Closed cycle and Binary system

Environmental Concerns Health effects of fluid emissions such as H2S Need to reinject produced fluids Well failures e.g. corrosion of tubing and casing; pollute groundwater; encounter magma/lava Possible catastrophic events e.g. blowouts, volcanic eruption, earthquakes, tsunami Venting Source: http://www.bigislandvideonews.com/2012/04/25/video-a-case-against-geothermal-part-one/, accessed 2-28-14

What is in Puna geothermal fluid? Water (liquid and steam) plus Benzene Hydrogen sulfide Fatal at 700 ppm PGV wells at 750 – 1100 ppm Ammonia Mercury vapor Methane Non-methane hydrocarbons Carbon dioxide Arsenic Radon Radionuclides (alpha and beta emissions)

Environmental Impact Environmentally friendly features noise reduction enclosures low-profile, small-footprint design near-zero emissions 100% geothermal fluid reinjection continuous monitoring

QUESTIONS? © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.

SUPPLEMENT © 2004 John R. Fanchi All rights reserved. Do not copy or distribute.