Advances in drill rig deployed radars
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ADVANCES IN DRILL RIG DEPLOYED RADARS. Mr Tim Sindle , ARCO/CRC Mining Imaging Lab, The University of Sydney Dr Carina Kemp, Business Development Manager, GEOMOLE. 11 th SAGA Biennial Conference and Exhibition, 16-18 September 2009. Outline. Introduction Method and Results

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ADVANCES IN DRILL RIG DEPLOYED RADARS

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Advances in drill rig deployed radars

SAGA, September 2009

ADVANCES IN DRILL RIG DEPLOYED RADARS

  • Mr Tim Sindle, ARCO/CRC Mining Imaging Lab, The University of Sydney

    Dr Carina Kemp, Business Development Manager, GEOMOLE

11th SAGA Biennial Conference and Exhibition, 16-18 September 2009


Outline

Outline

  • Introduction

  • Method and Results

    • Survey Gear Minimisation

    • Analyzing Drill Deployed Data

    • Automatic Algorithm Development

  • Conclusions

SAGA, September 2009


Introduction in mine geophysics

Introduction – In-mine geophysics

The Good

The Bad

  • Anticipate problems ahead of mining

  • Improve efficiency of mining operations

  • Bulky gear

  • Time consuming surveys cause delays in production

No matter how good the results, if any technique cannot be easily and reliably implemented in the mining environment,

it will not be used mainstream.

SAGA, September 2009


Introduction borehole radar bhr

Introduction – Borehole Radar (BHR)?

  • Ground penetrating radar (GPR) in a drillhole

  • Reflections indicate a contrast in the electrical properties of the rock.

  • BHR provides high detailed continuous reflections from lithology contacts and structures.

GeoMole BHR

  • 10 – 124 MHz Bandwidth

  • Resolution: less than1m

  • Range: up to 50m or more (depending on rock type)

  • Probe diameter: 32 mm

  • BHR Profiling at ~10 m/min

  • Omnidirectional antenna

SAGA, September 2009


Bhr then

BHR then….

  • Survey trials of BHR showed very promising results, but the gear let us down.

    • 50 kg optical fibre winch

    • 20 kg push rods

    • 10 kg probes

SAGA, September 2009


Bhr now minimal gear

BHR Now - Minimal Gear

  • Radar Tool

    • 1.6m

    • 3kg

  • Non-conductive spacers

    • 1.5m

    • 2kg each

  • Drill attachment

  • PDA

PDA

+

+

IQ

Drill

Attachment

Radar

Spacers

SAGA, September 2009


Bhr now drill rig deployed

BHR Now – Drill rig deployed

drill bit

spacers

Core barrel

IQ

SAGA, September 2009


Advances in drill rig deployed radars

Drill Rig Deployed Borehole Radar

- Pumpdown

The radar tool continuously records data.

The motion of the rods is discontinuous as the rods pulled and removed.

Spacers

Radar Tool


Deployment motion

Deployment Motion…

OTR Survey

Winch Survey

Moving

Moving

Measurement (station)

Measurement (Stationary)

Stationary

Depth

Depth


Radar data

Radar Data…

Winch Survey

OTR Survey

Stationary

Moving

Same 40m section of a horizontal borehole


Raw data

Raw Data

  • Aim: To understand the motion in order to work out how to recompress it.

  • Different motion for each type of drill-rig

Boart LM75 Diamond

SAGA, September 2009


Recompressing radar data

Raw Data

Recompressed Data

Recompressing Radar Data..


Movement log

Movement Log

  • Logging procedure tracks accurately the motion of the drill rig.

  • User records ‘MOVE’, ‘STOP’ and ‘ROD-CHANGE’ following the motion of the drill.

  • These events are time stamped and recorded for data processing

Accelerometers were installed in the radars to assist with movement logging

SAGA, September 2009


Time log processed data

Time Log processed Data

  • Vulnerable to human error

SAGA, September 2009


Automatic algorithm development

Automatic Algorithm Development

Using the accelerometer data for automatic processing:

  • Statistical deviation measurement

  • Fourier Spectrum Analysis

  • Velocity integration calculations

SAGA, September 2009


Statistical processed data

Statistical Processed Data

Standard Deviation

Threshold

Amplitude

Traces

SAGA, September 2009


Accelerometer processed data

Accelerometer Processed Data

  • Suffers from random accelerometer events

SAGA, September 2009


Fourier spectrum analysis

Fourier Spectrum Analysis

  • Examine the power in various regions of motion

  • Difference observed between some moving and stopped traces by examining the higher frequency content.

  • However, drill vibrations cause wide band energy gains.

  • METHOD ABANDONED

Frequency Spectrum

Stopped with drill shock

Start of move

Stopped

Constant velocity move

*

SAGA, September 2009


Velocity processed data

Velocity Processed Data

  • Noisy environment causes spurious accelerations and accurate velocity is hard to gather.

  • A high pass filter distributes the velocities aroundzero.

  • Then the mean representation of the velocity is calculated

Amplitude

Positive = Moving, Negative = Stopped

Trace

SAGA, September 2009


Velocity processed data1

Velocity Processed Data

  • Copes well with the sharp drill shocks and vibrations as they often have equal positive and negative direction.

  • Captures the start and stop of the movement well.

  • Particularly violent jerks can cause a trace to be lost.

SAGA, September 2009


Comparison

Comparison…

Accelerometer

Raw Data

Time Log

Velocity

SAGA, September 2009


Conclusions

Conclusions…

  • Drill deployed radars can be run with minimal disruption to normal work flow.

  • Using the time log alone can be vulnerable to human error

  • Yet all automated methods investigated so far are vulnerable to sharp spurious drill movements.

  • A combination of a time log together with statistical and velocity methods will result in smooth “winch quality” images being produced.

  • Development in this area continues

SAGA, September 2009


Conclusions1

Conclusions

  • The ultimate aim of a tool knowing its own position automatically is theoretically possible, but only within well defined constraints, and there will always be the unknown events on the drill rig that can cause inaccuracies.

  • The above progress makes it possible for quick data turnaround from survey to seamless integration of BHR data into mine planning packages, to enable day to day mining decisions to be made using such tools.

SAGA, September 2009


Acknowledgements

Acknowledgements…

  • The authors would like to thank DeBeers Canada in particular Kevin Smith, for their ongoing feedback and use of the tool.

  • The funding contributions of ARCO, CRC Mining, and GeoMole are gratefully acknowledged.

  • Many thanks to the tireless work by Sydney University ARCO Lab members including; Andrew Bray, Steven Owens, and Phillip Manning.

SAGA, September 2009


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