An example of Big Data Analytics in O&G Ecole des Mines de Paris - November 2014

Use of Big Data Analytics in O&G

Contents

Drilling Wells

Current Situation

Big Data Analytics

Pilot Study

Results

Use of Big Data Analytics in O&G 2

It is expensive to drill

It is even more and more expensive.

Drilling involves a large number of unknowns especially in

Exploration phase and a large number or parameters, mud

weight, torque, weight on bit, and so on.

Adjusting these parameters while drilling is a modern practice

because of downhole drilling measurements

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…and sometime drilling creates poor borehole conditions …

Poor boreholes are at the origin of:

Potential stuck pipe

More wiper trips

Cementing problems

Logging problem

Stuck, sticking tools, poor quality data, poor interpretation, poor decisions

Poor boreholes are due to:

Geology, eg: swelling shales

Rock properties

Deviation scheme

Drilling parameters

An analytical approach to the conditions causing stuck pipe, over large data volumes, taking into account a large number of parameters, has the potential to assist in the drilling model and the in-situ drilling parameters choice with a resulting decrease in the instances of stuck pipe.

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Sonic wrong-poor correlation

with seismic

Porosity wrong

Hydrocarbons wrong

Incorrect seismic processing may be done due to the bad hole interval

Expensive testing decisions may be made

Bad hole consequneces

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Evil is in the details and in the data format …

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• Volume

• Velocity

• Variety

• Veracity

Big data is about accessing structured and unstructured data

• RDBMS but also

• Social network, emails, knowledge DB, transactional DB, image, video, audio, GIS,

documents

… and then the big data …

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…it was in 2004, when Google published MapReduce

An appliance is a Hardware-Software system designed for performance,

scalability and analytics

…This architecture is now implemented in Appliances specifically designed for Big Data Analytics …

Aster functions

Example style for optional footer 10

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… this new architecture open new doors to analyse data …

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Sometimes because there is just too much data

Few links are created on the truly enormous scale, the entire North

Sea for example. Thousand of wells, thousand of 2D lines,

thousand of 2D km2 … is just too much for conventional analysis

techniques to handle in its enirety

But why it hasn’t been done before ?

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TERADATA

Data integration

Performance and

scalability

Advanced

analytics

Seismic

Well logs

Formations tops

Checkshot surveys

Pressures

Drilling data

Core data

Well test data

Completions

Production data

Fluid data

Cultural data

…So, to understand the reasons of bad hole occurrences on the UK Continental Shelf …

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CGG has access to data,

e.g. Drilling & Wells,

geology, petrophysics...

... and provides subject-

matter expertise to

interpret and enrich

the value of this data

Teradata

provides the analytical

platform to run complex

data analyses...

... and deliver deep data

science, math and stats

competences

… CGG and Teradata have been working on a common pilot…

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• Loading numerous different type de data

• Using different formats

• Linking the data types

• Using a ‘generic’ well data viewer

• Finding usable correlations

… and have solved together several challenges …

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This view was built using drilling

parameters and well logs directly

with Teradata technology – and

without the need for data

preparation, modelling and

indexation

• It is possible to load lots of differing types even with non

specific loading tools.

• All data is available from metadata such as Quad number to

individual logging curves.

• The manipulation and querying of data is done without any

preconception of the analysis to be made.

…initial data loading …

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… Vizualization using a generic tool …

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…Analyzing …

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• It is possible to use Big Data Analytics on diverse data type such

as employed in the Pilot

• Multivariate analysis are performed on the data without pre-

conceptions

• A variety of techniques are available to display multiple types of

data

• Unexpected correlations have been exhibited

• Correlations have been geo-localized across area and verticaly

across formation

• Correlations allow predictive statistics to be computed

• The Pilot confirms the possibility to improve the Drilling Models

using Big Data Analytics

… As a conclusion, we show that …

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• Possibility to perform the same pattern recognition in other

basins using public or corporate data

• Possibility to add some other input in the pilot (eg, deviation,

lihology …)

• Possiblity to query the data set using log curves

• Possibility to QC data and meta-data by pattern recognition

• Finally to analyse more data-type together give more value to

your decision.

…Our Pilot open the door for numerous other applications …

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• Aurelien.guichard@teradata.com

• Joe.johnston@cgg.com

If you want to try, to know more, to have a private demo, please contact: