E&P Big Data Pilot by CGG presented at SPE Student Chapter - Ecole des Mines de Paris - November 2014

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

2. 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&G2

3. 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
Use of Big Data Analytics in O&G3

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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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Big data is about:
• 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

9. 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 …

10. Aster functions
Example style for optional footer10

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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: