1 | US DOE Geothermal Office eere.energy.gov
Public Service of Colorado Ponnequin Wind Farm
Geothermal Technologies Program 2013 Peer Review
Decision Analysis for EGS Herbert H. Einstein Massachusetts Institute of Technology
April 22, 2013
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MIT
2 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Relevance/Impact of Research
OBJECTIVES CHALLENGE – How to develop EGS projects that are affected by many unknown and variable factors. Uncertainties, particularly those related to the subsurface, have a major effect on cost, time and resources associated with EGS development and operations. A large variety of uncertainties ranging from geological to constructional and operational have to be included. The research intends to develop tools, which allow one for formally assess these uncertainties and include them in expressions of risk.
3 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Relevance/Impact of Research
INNOVATIVE ASPECTS Integrated and effective fracture pattern – circulation model considering uncertainties. Well cost-time model considering uncertainties. Exploration and systems model for EGS. IMPACT Subsurface part of EGS, which is subject to the greatest uncertainties, can be related to time - and cost risks. Makes it possible to compare EGS projects on the basis of risk. All models based on easily accessible software.
4 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Scientific/Technical Approach
Principles of probability theory, decision making under uncertainty and formal uncertainty estimation have to be considered. This will allow one to systematically compare the wide variety of uncertainties and include them in an integrated expression of risk. Reliance on these basic scientific and methodological principles will ensure the rigor of the approach. Reliance on estimates/tools and models that have been developed at MIT and practically applied will ensure the technical feasibility. For example: • Fracture pattern – and, eventually, flow/circulation models capture the relevant
geologic uncertainties. • Construction cost/time models can be adapted for geothermal well time/cost
estimation. • Systems model can integrate any set of other models
5 | US DOE Geothermal Office eere.energy.gov
The model development and integration will be approached through a set of scientifically defined tasks.
1. Fracture Pattern Model for EGS
2. Drill Cost and Time Model Considering Uncertainties
3. Circulation Model for EGS
4. Subsurface Time/Cost Model
5. Exploratory Model for EGS
6. Systems Model
Combine 1-5 and Technology Transfer
Enhance Surface Part of Model
Results will be presented in the following order:
1 and 3 together – then 2.
DECISION ANALYSIS FOR EGS Scientific/Technical Approach
6 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
STOCHASTIC FRACTURE PATTERN MODEL - GEOFRAC
Sousa et al. 2010
primary process Poisson Planes
secondary process Voronoi Tessellation
tertiary process Translation & Rotation of Polygons
GEOFRAC’s stochastic processes were implemented and optimized in MATLAB.
7 | US DOE Geothermal Office eere.energy.gov
MATHEMATICS GEOFRAC PARAMETERS FRACTURE PROPERTIES
µ d, θ, φ( )= µfθ ,φ θ, φ( )µ – Poisson plane intensity fθ,φ(θ,φ) � orientation p.d.f.
Poisson planes
E[A] = 1/λ
σΑ=0.529/λ2
λ – Poisson point intensity
Voronoi Tessellation
P32 =Af , i
i =1
N
∑V
P32 – Fracture intensity
E[A] – Mean fracture area
P32 = µ
E[A] = 1/λ
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
FRACTURE PATTERN AND CIRCULATION MODEL
8 | US DOE Geothermal Office eere.energy.gov
FLOW-PATH CONTRIBUTING FRACTURES
FRACTURE APERTURES: deterministic and probabilistic modeling of fracture aperture. “CLEAN” FRACTURES: retaining only fractures that contribute to flow paths, i.e., those intersecting at least (1) two other fractures, or (2) a fracture and a boundary of the model.
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
FLOW PATH COMPUTATION
-20-10
0
1020 -10 -8 -6 -4 -2 0 2 4 6 8 10
-2
0
2
4
6
8
10
YX
Z
9 | US DOE Geothermal Office eere.energy.gov
branch no. 1
branch no. 2
branch no. 3
branch no. 4
branch no. 5
Middle point of intersection between fractures Intersection nodes (between branches) Initial nodes (injection boundary
Final Nodes (production boundary)
-5
0
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-5
0
5-2
0
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4
6
8
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314
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77
376
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X
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Z
-6 -4 -2 0 2 4 6-6
-4
-2
0
2
4
6
X
Y
• Middle point of intersection between
- Fracture Length
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
Fracture Length Idealized Branch
10 | US DOE Geothermal Office eere.energy.gov
Cibich, 2008
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
50m
Flow between HDR-2a and HDR-1
100m
100m
Geofrac Input
(assumptions):
P32=1
E[A]=300m2
h=0.5mm
Fisher distribution (k=10)
-50-50
500
50
Simplified flow network (centerline of flow paths)
APPLICATION TO HIJIORI EGS - JAPAN
Q(l/s)
Flow rate histogram
11 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
Thermal Circulation Model Basics - Parallel Plate fluid flow ( Gradient, Roughness) Velocity profile - Reynolds Heat transfer (solid, fluid) – Biot Time dependence – Fourier Lateral motion – Prandtl Boundary solid/fluid – Nusselt
Create starting (parent) nodes
Create nodes Calculate heat transfer
Create daughter arcs
Structure of Model
12 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
Drill Cost, Time and Cost Model Considering Uncertainties Develop existing Decision Aids for Tunneling (DAT) to consider for a geothermal well: - Various drilling, logging, casing stages - Component costs and uncertainties (Labor, Material, Equipment) - Trouble costs and uncertainties (Fishing, Stuck Drill Pipe, Casing
Failure) - Geologic features and uncertainties (Effect of strength and
abrasivity on drill time and bit life) - Temperature related failures and uncertainties (effects on logging,
fluid loss and cementing) Note: Other parameters can be included.
13 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
Drill Cost, Time and Cost Model Including Uncertainties Example application to Sandia (Polsky et al., 2008) Case
Sandia Well Network
14 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS Accomplishments, Results and Progress
Activity Network for the Surface Drilling Method (DAT Screenshot).
Cost-Time Scattergram for Combined Parametric Study. 1000 construction simulations were performed, taking into account component cost uncertainty, trouble events, geological variation, and drilling fluid usage rates.
15 | US DOE Geothermal Office eere.energy.gov
DECISION ANALYSIS FOR EGS SUMMARY
SUMMARY OF MAJOR ACHIEVEMENTS Stochastic Fracture Pattern Model Circulation (Flow and Heat Exchange) Model Well Cost/Time Model All the above have been validated. All the above consider uncertainties. All the above are easily useable (Matlab or otherwise available software). The final steps – exploration and systems model have been started based on the above. It is thus possible to say that significant impact on the DoE Geothermal Energy Office’s mission and goals has been achieved through: Decision Making Tools for Assessing, Analyzing and eventually Reducing the Time - and Cost Risk of the Subsurface Part of EGS.
16 | US DOE Geothermal Office eere.energy.gov
Timeline: Budget:
• Funds used to support:
- Postdoctoral Associates, Graduate Research Assistants, Undergraduate Research Assistants, PI
- These participants worked in close day-to-day interaction • Interaction with other research at MIT
- Close interaction with EGS mechanics oriented research • Interaction with Industry:
- Contacts made to get data.
Project Management
Federal Share Cost Share Planned Expenses to
Date
Actual Expenses to
Date
Value of Work Completed
to Date
Funding needed to
Complete Work
549,148 54,487 ~480,000 480,000 SAME ~120,000
Planned Start Date
Planned End Date
Actual Start Date
Current End Date
12/29/2009 01/31/2014 02/01/2010 01/31/2014
