capture and geological data extraction: tools for a...

CAPTURE AND GEOLOGICAL DATA

EXTRACTION: TOOLS FOR A BETTER

ANALYSIS AND DIGITAL MODELLING

UNIVERSITAT DE BARCELONA

U

BDavid García-Sellés

Pablo Granado

Oscar Gratacos

Núria Carrera

Pau Arbues

Digital Workflow

Outcrop

Digital Capture

Data Extraction

Inte

rpre

tati

on

A

na

lysis

F

ield

Wo

rk

Lidar

Photogrammetry

Million coordinates XYZ

Reflectivity

Texture color

Remote Sensing

Petrel, Move, Fracaflow Structure

Specific Modules

Rock slope

instability

DFN Digital

Fracture Network

Surfaces

Lineations

Digitalization

from 2D to 3D

Semi-automated

Supervised method

Specific Software

Capture Digital Outcrops

Lidar Equipment

Electric generator Laser scanner

Antenna

and DGPS

receiver

Digital camera calibrated

FIE

LD

WO

RK

Lidar Processing

Image 1 Image 2 Image 3

Requires logistical

High data quality

Total reliability

For advanced users in:

GPS differential, post-

processing Lidar data.

Añisclo anticline, Pyrenees. Paleocene

limestones

FIE

LD

WO

RK

GPS device

Photogrammetric SfM Equipment

Digital Camera

FIE

LD

WO

RK

Photogrammetric SfM Equipment

GPS positioning

attached to file picture

(exif).

Poor precision

must be

compensated

by a good

distribution of

photo-shooting

FIE

LD

WO

RK

Photogrammetric SfM Processing

Fast acquisition

Cameras position

distribution

Standard camera

Camera position Abra del Condor anticline, Bolivia. Sub Andean

Range. Sandstones

FIE

LD

WO

RK

Photogrammetric Model in Render view

Medium-high data

quality in accuracy

and density

Uncertain result

All users

FIE

LD

WO

RK

Abra del Condor anticline, Bolivia. Sub Andean

Range. Sandstones


Abra del Condor anticline, Bolivia. Subandean

Range. Graystones

FIE

LD

WO

RK

Photogrammetric Model in Photorealistic view

Medium-high data

quality in accuracy

and density

Uncertain result

All users

As a payload


Photogrammetry Vs Lidar

Differences in GPS devices: Scale Azimuth Dip Positioning

Lidar Model Photogrammetric Model

FIE

LD

WO

RK


Range. Sandstones

Photogrammetry Vs Lidar

Differences in GPS devices: Scale Azimuth Dip Positioning

FIE

LD

WO

RK


Range. Sandstones

Photogrammetric Vs Lidar

Offset corrected

FIE

LD

WO

RK


Range. Sandstones

Photogrammetric Vs Lidar

1 m

Comparative profile: Lidar Model – Photogrammetric Model

FIE

LD

WO

RK

Alignment histogram models


Range. Sandstones

Data Extraction from High Resolution Models

Surfaces

Simplified geometric

surfaces Point Cloud

Data extraction: Vectorizing point clouds algorithm I

NT

ER

PR

ETA

TIO

N

Stereoplot

Dip

- Points by regression

- Degree of fit (coplanarity, M)

- Reliability (colinearity, K)

Parameters obtained: - Vector orientation Azimuth

Point Cloud

Data extraction from surfaces: Planar regression by Moment of Inertia analysis I

NT

ER

PR

ETA

TIO

N

Dip

- Points by regression

- Degree of fit (coplanarity, M)

- Reliability (colinearity, K)

Parameters obtained: - Vector orientation Azimuth

Stereoplot

IN

TE

RP

RE

TA

TIO

N

0

2

4

6

8

10

12

14

16

18

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Mil

lio

n p

oin

ts

Time processing (hour)

Data extraction from surfaces: Outcrop vectorization

Coplanarity Index

0 6.2 x

Data extraction from surfaces: Planar regression by Moment of Inertia analysis

Coplanarity Index mask

0 6.2 x


Colinearity Index

0 2 x


Colinearity Index mask

0 2 x


Data extraction from surfaces: Outcrop vectorization

Outcrop section in detail

IN

TE

RP

RE

TA

TIO

N


Range. Sandstones

Data extraction from surfaces : Azimuth –Dip classification by sets

Fracture Sets

IN

TE

RP

RE

TA

TIO

N

Data extraction from surfaces : Isolate clusters-Reconstruct surfaces

Fracture Sets

IN

TE

RP

RE

TA

TIO

N

Data extraction from surfaces : Isolate patches-Reconstruct surfaces

Morphological Model

IN

TE

RP

RE

TA

TIO

N

Data extraction

Point cloud area

RGB Image

IN

TE

RP

RE

TA

TIO

N

High Resolution Model in render view

Geological feature as

geometric lineation or

geometric surface

High Resolution Model

Image outcrop

IN

TE

RP

RE

TA

TIO

N Data extraction from lineations: Image-Model link by Colinearity equation

Image coordinate Xi, Yi Model Coordinate: Xm, Ym, Zm Camera position

Cotiella Massif, Pyrenees. Cenomanian

limestones

Camera orientation

Focal length, lens distortion

IN

TE

RP

RE

TA

TIO

N Data extraction from lineations: Software implementation


limestones

IN

TE

RP

RE

TA

TIO



limestones

Set 0

Points Selected by digitalizing

Planar regression calculated by the Inertial Moment

Azimut

Dip

- Number of used points

- Degree of fit (coplanarity, M) - Reliability (colinearity, K)

Parameters obtained:

- Vector orientation

- Trace length

Stereoplot

IN

TE

RP

RE

TA

TIO



limestones

Image coordinate Xi, Yi Model Coordinate: Xm, Ym, Zm

Selected points respect to line distance tolerance in order to model density

IN

TE

RP

RE

TA

TIO

N Data extraction from lineations: Image advantages


limestones

IN

TE

RP

RE

TA

TIO

N Data extraction from lineations: IR image


limestones

IN

TE

RP

RE

TA

TIO

N Data extraction from lineations: Photogrammetric solutions, orthoimages


limestones

Digitalization at field, before acquisition

or at desktop, after processing High Density Model

Analysis

Surface Detection: Isolate patches-Reconstruct surfaces

Plane Orientation

Centroid

Points used

Rughness

Approachs in

Wide

Long

Area

Morphological model

IN

TE

RP

RE

TA

TIO

N

Surfaces

Lineations

Plane Reconstruction

Morphological Model

Analysis: Morphological model for analysis

0123456789

10111213141516

Number of fractures/m

Number of fractures/m Scanline data:

Spacing Mean

Number of fractures / Scanline

Density of fractures

Orientation Mean

Frequency: Area, spacing....

AN

ALY

SIS

Analysis: Morphological model

Histograma of logarithmic base for plane area and set

AN

ALY

SIS

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