Uncertainty in seismic interpretation - what factors influence interpretational ability?

Clare Bondclare.bond@abdn.ac.uk

Zoe Shipton, Alan Gibbs, Serena Jones, Rebecca Lunn, Euan Macrae, Frank Richards, Nicholas Richardson

Politics

Fashion

Fieldwork as a training toolEnables us to make predictions – a natural lab for formulating and testing hypotheses

Twice folded quartzite beds in Donegal Bog - Geoff Tanner

Fieldwork

Geological Datasets - spatially limited data, collected in different dimensions

Often data is collected by remote sensing

Uncertainty

Hard data and soft data is combined and used to make predictions and interpretations

Data collection, processing and interpretation all have an inherent uncertainty

Data / Imagery is only as good as the model on which it is based

Uncertainty

Concepts - are applied to data during interpretation

Concepts are based on analogues formed from previous experience: direct personal experience and indirect gained from others

Concepts

Interpretation

How uncertain are we?

Data will support a number of solutions

Some solutions are invalid

The valid solutions are non-unique

Non-unique solutions

Non-unique solutions

No, it’s a hanging wall anticline with growth strata

It’s an inverted roll-over

It’s……. time for beer

1975 2D Seismic Line though South Brae

Non-unique solutions

1981

Geological cross-section through South Brae

Non-unique solutions

Harms et al.

1983Planar Faults

Non-unique solutions

Gibbs

Non-unique solutions

1984 Alternative Graben Margin Structures – Listric Faults

Gibbs

1988North Brae & Beinn Structures - Dip-Slip Extensional Model

Beinn Field

North Brae Field

NW SE

Non-unique solutions

Beach Associates

Line 541

BALDER

LOWER CRETACEOUS

EKOFISK

BCU

Base Cretaceous Time Structure

N.Brae

C.Brae

S.Brae

Non-unique solutions

1991Inversion

Russell

Changing the Brae concept modeldid not change the outcome

But, changed the thought processes and understanding

Impact on outcome?

Salt loading & doming

x2 vertical exaggeration

ENEWSW

Extension and slumping on top saltSalt domes – passive down-building

16

0

Dep

th, k

mConcept change - revolution

Salt welds

x2 vertical exaggeration

ENEWSW

36km extension on northern end of Miocene ‘trough’

Good quality deepwater depth seismic data images compressional belt at the deformation front

extension, rafts, thin/welded autochthonous saltcompression, salt canopies

16

0

Dep

th, k

mConcept change - revolution

Changing the Gulf of Mexico concept model changed the outcome

And the thought processes and understanding

Kuhn, T.S. 1962 The structure of scientific revolutions

Impact on outcome!

Silver Pit

Controversy and uncertainty – non unique solutions

Salt tectonics?

Impact tectonics?

Stewart & Allen (2002) Nature

Underhill (2004) Nature

Psychology

Tverskey and Khaneman, Science (1974)"Judgment Under Uncertainty: Heuristics and Biases”

Khaneman – nobel laureate (economics) for his work with Tverskey in 2002.

Looked at the psychologies of making decisions from uncertain datasets – including the use of ‘rules of thumb’ (heuristics) and the impact of bias, introducing the idea of anchoring.

Psychology

Heuristics and biasesHuman Bias DescriptionAvailability bias The decision, model or interpretation that is most readily to

mind, or dominant

Confirmation bias To seek out opinions and facts that support ones own beliefsand hypotheses

Anchoring bias Failure to adjust from experts’ beliefs, dominant approaches or initial ideas

Optimistic bias It won’t happen to me mentality (or there is definitely oil in this prospect!)

Positive outcome bias Wanting things to turn out for the best and putting the most positive spin on data interpretation

Hypothesis testing bias Starting with an initial hypothesis and trying to fit the data to it (similar to confirmation bias)

Bond et al., (2008) after Krueger and Funder (2004)

Human bias

Filling in the Gaps

human bias and conceptual models

Filling in the Gaps

human bias and conceptual models

human bias and conceptual models

A small experiment

Whos Biased?

Was it an impact crater?

human bias

It’s my sweet Satan. The one who’s little path would make me sad whose power is Satan.

Oh he’ll give you, give you, 666.

There was a little toolshed, where he made us suffer, sad Satan.

www.reversespeech.com

Is it an impact crater?

We are all biased

Stewart (1999)

Petroleum Geoscience

1:2 chance of an impact crater in the North Sea

Stewart open to the idea of an impact crater

We are all biased

We are all biased

What Allen saw looked like a crash site. “Iwas flabbergasted”, he says. “I’d neverseen anything like it”. It wasn’t until ameeting with Simon Stewart, a BPstructural geologist who also thought itlooked like a crater, that Allen took the ideaseriously.

Silver Pit

We are all biased

Salt tectonics?

Impact crater?

expectation

Fashion Human Bias

Experience Knowledge Personality Psychology

Interpretation is subjective

Subjectivity

Opportunities for Uncertainty

• Objective and subjectivity uncertainty in seismic image data and interpretation

Image: VSA

Plenty of opportunity for uncertainty in industrial structural geology – both objective and subjective

Why Seismic Images?• Commonly used in geoscience industry

• Represent the uncertainty common in geological datasets

How do geoscientists deal with the uncertainty of there not being a right answer?

Human nature - the ditherer and the decisive... Are you someone who draws dashed lines on your map and dare not ink it in?Or do you... grab the pen and go for it, potentially regretting it later?

Not clear that we understand well what makes an individual effective at dealing with such uncertainty.

Never mind how to teach,or deal with it.

That’s why it’s called interpretation

Geology and Petroleum GeologySchool of Geosciences

Rankey and Mitchell, The Leading Edge (2003). That’s why it’s called interpretation: Impact of horizon uncertainty on seismic attribute analysis.

Rankey and Mitchell (2003)

“Artistic license of the interpreter will be revoked entirely by the year 2000.... There will be so much data [in 3D seismic] that you will simply follow the mechanics of what the data set reveal to you.” Marion Bone, SEG Past-President (quoted in Johnston, TLE, 1994)

Rankey and Mitchell (2003)

Geology and Petroleum GeologySchool of Geosciences

Key findings“Seismic interpretations likely are based on previous experiences, preconceived notions, types of data available, data quality, and geologic understanding.”

“Uncertainty in interpretation should be evaluated and minimized using geologic insight, analysis of end-member possibilities, and seismic modeling.”

Evidence for anchoring “I did ... not want to change any of my picks based on the additional well data—looks like I had it nailed.” - but only on a small sample of 6 interpreters.

Other papers

Geology and Petroleum GeologySchool of Geosciences

Polson and Curtis (2010)Seismic interpretation – elicitationDynamics of uncertainty in interpretation, the spread of prior knowledge and subjectivity of individuals, disagreement and confidence (4 individuals).

Bond et al. (2008) and Rowbotham et al. (2010)Multiple scenarios advocated, rather than single deterministic models

Bond et al. (2011)Seismic interpretation – experience cohortsAnalysis of the change in approach and confidence of individuals interpreting with experience (36 individuals).

Chellingsorth et al. (2011)Top reservoir map from wells and outcrop – 4 individuals to calculate volumes.

Richards et al. (2015)Geo seismic interpretation – by 8 groups to create a top reservoir map from an intersecting 2D grid.. Risks to predicted volumes highlighted.

How many different interpretations?

Experimental evidence

Seismic created from known model

Odin project used synthetic seismic based on a structural model created by forward modelling to test subjective spread in interpretation

Synthetic seismic

Experiment 1

What influences the interpretation?

– Competence

– Level of Experience

– Field of expertise

– Personality and problem solving approach

– “Cultural” background

Experiment 1

One dataset – many conceptsExperiment 1

Many structural modelsExperiment 1

1) multiple conceptual models can be applied to the samedataset (conceptual uncertainty)

Experts - model or data driven?

24 experts at the AAPG DWFTB Hedberg 2009 interpreted the seismic dataset.

Concepts vs data

Expert- experienceStructural geology experience -specialist c.60%

Seismic interpretation experience -good working knowledge c. 65%

Interpretation frequency - daily c. 40%

Experiment 2

Torvela and Bond (2011). Journal of Structural Geology

Experiment 2

Diversity and Spatial Correlation of Interpretations

Different styles and formsDifferent interpretations of faults and distributed deformationDifferent implications for the structural evolution

Experiment 2

Dominating models

Trishear model most dominant.

Experimental 2

2) even when the concept is universally recognised (e.g. fold-thrust belt) and the imagery is of good quality large uncertaintiesin fault placement exist and the resultant implied mechanisms of structural evolution cover a broad range.

Effect of Prior Knowledge?

Student –MSc sequence stratigraphy

Student – PhD salt tectonics

Anecdotal – evidence from the results….

But what about statistically?

Experimental evidence – experiment 1

Effect of Prior KnowledgeDominant Tectonic Expertise - more likely than others to produce an interpretation based on this expertise (i.e. dominant thrust tectonic experience - 29% produced a thrust interpretation, compared to 27% of participants with other expertise). BUT not statistically significant.

Length of Experience - had no obvious overall effect (i.e. students were just as likely as those with 15+ years experience to produce an incorrect interpretation, 76%).

Experiment 1

23%27% 35%

184

Self-defined experts in structural geology

445

Experiment 1

TechniquesEffective expertsuse lots of techniques.

100%

79%67%

23%18%

35%

Experiment 1

Specific Techniques

35%

94%

44%51%45%37%

10%

Effective expertsused specific techniques –notably thoughts about the geological evolution (reasoning).

Experiment 1

Statistically significant factors amongst structural geologistsMaster’s or Ph.D. degree 0.0055 Odds Ratio: 7.16Horizons 0.0010 Odds Ratio: 4.13Annotation 0.0107 Odds Ratio: 2.69Geological evolution 0.0007 Odds Ratio: 40.51

Experiment 1

“those who used evolutionary thought processes in the form of sketches or textwere >40 times as likely to produce the correct interpretation than those that had no Master’s or Ph.D. degree and used none of the three significant techniques, which translated into 94% of experts who used it being successful.” Bond et al., 2012.

Bond et al. (2012), Geology.

Non-expertsEveryone can be an expert?

27%

87%

37%40%

7%

38%30%

Experiment 1

Everyone can be effective by using multiple techniques to query the data and applying specific validation techniques (reasoning).

But not many people are:

of the 184 experts only 18 (c.10%) showed evidence of thinking about the geological evolution.

Odin Experiment - ConclusionsExperiment 1

Geological Reasoning

Reasoning

Frodeman (1995) Geological reasoning: Geology as an interpretive and historical science

Regional and horizon correlation - seismic strat’ matching

A B

AB

Geological Reasoning

Reasoning

AB

3) experience is not a substitue for good technique use, or more specifically the application of geological reasoning skills.

Geological Reasoning – is it really effective?

Reasoning - the test

Euan Macrae (2013). Unpublished PhD thesis

Reference Experts 1-3Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Reference Experts 4-6Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Reference Expert’s Key Features

Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Key Feature Score’s for 444 interpreters

Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Controlled experiment

Control group – “Please interpret whole seismic image” as the main surveyTest group - “1. Interpret the whole seismic image. Please focus your interpretation on the geological evolution of the section. 2. Summarise the geological evolution below.”

Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Key Feature Score’s for controlled experiment

Experiment 3

Euan Macrae (2013). Unpublished PhD thesis

Explicit reasoning

4) use of effective techniques results in better seismicinterpretation outcomes.

Evidence from our controlled workshop experiment suggests that reasoning through the geological evolution should be an explicit process, to ensure that it is undertaken fully, requiring geoscientists to challenge themselves to verify, and hence produce better, interpretations

Creative space for reasoning

Creativity

Bond et al. (2015)

More white space – better models?

Creativity

More white space – better models?

Creativity

69%

21%

Top reservoir maps

2d-3d

8 groups – 8 top reservoir maps

Posted Data from seismic Interpretation Top Reservoir point depth posted at grid intersection points and interpreted contours. Units = meters.

860780 825765770

770 790 820 845 880

795 810 835 870 910

800 820 850 880 920

800

800

750

825 860 895 920 960

955

940

920

900700

770

780

890 890

Richards et al., (2015)

Simple seismic sections2d-3d

Top Reservoir

S N

Mapped fault variability2d-3d

A B

4-5

3

2

1

0

Number of fault cuts

3 4

0

50

100

150

200

250

65 6556 56 54 54 53 53 50 50 53 53 58 58

18 1825 25

20 32

17 28

27 27 32 32 18 18 7 7

1012

9

2

1316 16 14

7 713

57 7

9.5 202

28

28

10

18

12

40 13

3331

31

614

10

109

9

10

10

10

11

11

12

20 20

10

10

5

105

5

4.7

9

4

3

3

6

4

4

5

4

2

15

5

3

20

19

19

A B1 B2 C D E1 E2

E3 F G H I J K

L M N O P

A AA

A A AA

B B

BB

B B B

EE

EE

E

MAP 1

> 20m throw

MAP 2

> 20m throw

MAP 3

> 20m throw

MAP 4

> 20m throw

MAP 5

> 20m throw

MAP 6

> 20m throw

MAP 7

> 20m throw

MAP 8

> 20m throw

KM2

G/3E/7

C/7

F/4H/3

I/3

A/7

B/8

D/3

K/3J/4

L/3M/2

N/1

O/1

P/1

A

CC

α α α α ααα α

B

No. and volumetrics of traps

Risking – top reservoir maps2d-3d

5) reasoning techniques can be used to risk models.

The multiple interpretation challenge

Creativity

Rabbit or duck Or Duck and rabbit?

The Importance of Creativity Wiseman et al. (2011)

Generating• Using one or more geologists with a range of prior knowledge,• Exposing geologists to a range of concepts prior to interpretation,• Removing regional and tectonic context, and• Encouraging multiple interpretations.

Assessing• Using structural reasoning evolution and restoration techniques to determine

model viability,• Considering regional and tectonic context,• Use of peer review and specialist technical assurance, and• Assessment of play impact.

Generating and Assessing Interpretations

Improved outcomes

Thoughts

Interpret datasets with the integrity of the final solution in mind.Don’t need to be a specialist - but do need to be able to apply knowledge, concepts, techniques - reasoning to the problem.Ability to question the data and the model - fresh eyes and creativity.

“It is likely that this type of reasoning will become more crucial in the next century. Many of the issues we face (global warming and various types of

risk and resource assessment) are by their nature both scientific and ethical, with the scientific aspect of the problem deeply influenced by

interpretation and uncertainty.”

Frodeman (1995) on Geological Reasoning