Fast modelling of Airborne EM data using "Smart Interpretation"
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Transcript of Fast modelling of Airborne EM data using "Smart Interpretation"
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…by I•GIS
Presented at the 2015 AGU meeting in San Fransisco
Smart Interpretation – application of machine learning in geological interpretation of AEM data
Torben Bach 1, Rikke Jakobsen1, Tom Martlev Pallesen1, Mats Lundh Gulbrandsen2, Thomas Mejer Hansen2, Anne-Sophie Høyer3, Flemming Jørgensen3
1. GeoScene3D Team, I-GIS, Risskov, Denmark2. Niels-Bohr Institute, Computational Geoscience, University of Copenhagen, Denmark3. Geological Survey of Denmark and Greenland (GEUS), Denmark
The ERGO project: Effective High-Resolution Geological Modeling
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…by I•GISOutline
Presentation outline
• Motivation behind and Introduction to “Smart Interpretation”
• Workflow when modelling with “Smart Interpretation”
• Case Example, Gotland, Sweden
• Summary and outlook
Introduction Workflow Test Case Summing Up
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…by I•GISMotivation
Motivation for Smart Interpretation (SI)• Observations:
• Large AEM surveys - enormous amount of data.• One the one hand - manual interpretation is time consuming• On the other hand - geophysical resistivity is not necessarily linked to geological formation or
lithology • A Geological expert is needed.
• Inspiration: Seismic Auto-picker, used daily as a standard part of modelling of seismic data in O&G
• Goal: Develop a practical and usable tool for assisting the Geologist
Introduction Workflow Test Case Summing Up
Autumn Spring
20 50 ohmm
Sand and Clay have overlapping resistivitiesSeasonal variation is reflected in resistivities
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…by I•GISSI - Theory
Steps• Infer a statistical model h(d|M)• Solve the problem: d = f (M).• Perform predictions dpred with uncertainty
Mpred
dpred
f(M)
h(dpred|Mpred)
+/- 1 std.
M
d
Our Toolbox• Standard Gaussian based inversion theory – with a twist…**
Benefits compared to other Machine Learning techniques:• Tools for analysing parametric covariances and interdependencies• A measure of uncertainty on the estimates• Very fast !
**See ”Smart Interpretation - Automatic geological interpretations based on supervised statistical models” byGulbrandsen, Cordua , Bach and Hansen, currently subitted and in review for ”Computational Geosciences”
Introduction Workflow Test Case Summing Up
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…by I•GISSI - Theory
M
Geophysical Data (M)
Introduction Workflow Test Case Summing Up
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…by I•GISSI - Theory
M d
Geophysical Data (M)
Geological Knowledge (d)
Introduction Workflow Test Case Summing Up
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…by I•GISSI - Theory
M d
h(d,M)
Geophysical Data (M) Statistical Model
h(d,M)
Geological Knowledge (d)
Introduction Workflow Test Case Summing Up
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…by I•GISSI - Theory
M d
h(d,M)
Mpred
dpred
Geophysical Data (M) Statistical Model
h(d,M)
Geophysical Data Elsewhere
Mpred Predicted Geology with uncertainty
h(dpred|Mpred)
Geological Knowledge (d)
Introduction Workflow Test Case Summing Up
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…by I•GIS
1:Add manual interpretation
2:Run SI Locally3:Apply
algorithm globally
4:Evalute and QC result
Introduction Workflow Test Case Summing Up
Workflow in Production
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…by I•GIS
Groundwater mapping on the Island of Gotland
Courtesy Peter Dahlquist, SGU
Test Case
Introduction Workflow Test Case Summing Up
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…by I•GISTest Setup
Introduction Workflow Test Case Summing Up
The Geologists• Geologist 1: Using normal manual modelling• Geologist 2: Using SI assisted manual modelling
Limestone
Marlstone
Clay- and marlstone
The Geology
Sharp boundary
Diffuse Zone
The Test• Compare ”Manual Model” to ”Model generated using 10% as input to SI”
• Compare ”Manual Model” to ”SI assisted Model”
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…by I•GIS
Reference Model
The manual model
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…by I•GISTest: Manual Model
Introduction Workflow Test Case Summing Up
Surface 2Surface 1
Geologist 1 – a standard manual model
• Evenly distributed mesh of manual interpretation points• Surfaces dipping trend towards the south-east• Abrupt high in north-west
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…by I•GISTest: Manual Model
Introduction Workflow Test Case Summing Up
The Geologist avoids couplings and artifacts in data
Difuse ZoneInterpreted
The Geologist models the ”pinch out” of the ”diffuse” layer
Geologist 1 – a standard manual model
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…by I•GIS
TEST 1
Throw away 90% of the Geologists input
– and run Smart Interpretation
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…by I•GISTest: SI using 10% of Manual Model
Introduction Workflow Test Case Summing Up
• General trend in surfaces is reproduced• Higher small scale variation due to the increased amount of interpretation points
Surface 2Surface 1Manual Manual
MANUAL
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…by I•GISTest: SI using 10% of Manual Model
Introduction Workflow Test Case Summing Up
• General trend in surfaces is reproduced• Higher small scale variation due to the increased amount of interpretation points
Surface 2Surface 1Manual 10% of manual points, 1688 SI points generated
Manual 10% of manual points, 1653 SI points generated
Smart Interpretation
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…by I•GISTest: Reduced Model 10%
Introduction Workflow Test Case Summing Up
Geologist 1 Remove 90% of interpretation points – and run SI
10% Manual + SI26 man.points, 1653 SI.points
Difference
Surface 1264 points
343 points
Surface 2
Manual Model+/- 10 m
26 man.points, 1688 SI.points
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…by I•GIS
Manual
Test: SI using 10% of Manual Model
Introduction Workflow Test Case Summing Up
Manual
MANUAL
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…by I•GIS
Manual
Test: SI using 10% of Manual Model
Introduction Workflow Test Case Summing Up
10% of manual points
Manual10% of manual points
Couplings only partly managed
Difuse ZoneIs managed
Pinch Out is managed
Smart Interpretation
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…by I•GIS
TEST 2
A model build using Smart Interpretation
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…by I•GISTest: SI Assisted Model
Introduction Workflow Test Case Summing Up
• General trend in surfaces is reproduced• Higher small scale variation due to the increased amount of interpretation points
Surface 2Surface 1
Manual Model Manual Model
MANUAL
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…by I•GISTest: SI Assisted Model
Introduction Workflow Test Case Summing Up
• General trend in surfaces is reproduced• Higher small scale variation due to the increased amount of interpretation points
Surface 2Surface 1
Manual Model Manual ModelSI Assisted Model SI Assisted Model
Smart Interpretation
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…by I•GIS
Manual
Manual
Test: SI Assisted Model
Introduction Workflow Test Case Summing Up
MANUAL
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…by I•GIS
Manual
Manual
Test: SI Assisted Model
Introduction Workflow Test Case Summing Up
SI Assisted Model
SI Assisted Model
Couplings are managed
Difuse ZoneIs managed
Pinch Out is managed
Smart Interpretation
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…by I•GISTest: SI Assisted Model
Introduction Workflow Test Case Summing Up
Summary• The theoretical framework derived from Gaussian based inversion techniques
• It is very fast• calculation uncertainty
• Test case shows ability to map couplings and diffuse geological boundaries• More interpretation points -> more variation in the generated surfaces• Implemented in production software GeoScene3D
Looking ahead…• Currently underway
• developments toward looking for “structures” in data• other attribute types, e.g. coherency• other datatypes included in SI
Come and join us
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…by I•GIS
Thank You !