Fast modelling of Airborne EM data using "Smart Interpretation"

…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

…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

…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

…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

…by I•GISSI - Theory

M

Geophysical Data (M)

Introduction Workflow Test Case Summing Up

…by I•GISSI - Theory

M d

Geophysical Data (M)

Geological Knowledge (d)

Introduction Workflow Test Case Summing Up

…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

…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

…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

…by I•GIS

Groundwater mapping on the Island of Gotland

Courtesy Peter Dahlquist, SGU

Test Case

Introduction Workflow Test Case Summing Up

…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”

…by I•GIS

Reference Model

The manual model

…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

…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

…by I•GIS

TEST 1

Throw away 90% of the Geologists input

– and run Smart Interpretation

…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

…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

…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

…by I•GIS

Manual

Test: SI using 10% of Manual Model

Introduction Workflow Test Case Summing Up

Manual

MANUAL

…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

…by I•GIS

TEST 2

A model build using Smart Interpretation

…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

…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

…by I•GIS

Manual

Manual

Test: SI Assisted Model

Introduction Workflow Test Case Summing Up

MANUAL

…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

…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

…by I•GIS

Thank You !