An effective G&G exploration strategy inspired by a wolfpack · An effective G&G exploration...
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An effective G&G exploration strategy inspired by a wolfpack
N.M. Hernandez, F.Baillard, I. Panganiban, K.G. Maver
20 September 2019, StavangerFORCE Machine Learning Conference
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Outline
• ElasticDocs Technology Review
• Current Developments & Practical Applications
• Strategy for Breaking Cognitive Barriers in Exploration• Knowledge Network
• Native Language Understanding
• Conclusions
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Four Pillars
• Optical Character Recognition• Natural Language Processing• Deep Neural Networks • Geolocation & ElasticSearch
for Processing Unstructured Geoscience Data
So, last year
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40,000DOCUMENTS
500,000IMAGES EXTRACTED
100 yearsHISTORY
5
TeraBytes
100+
DOCUMENTS CATEGORIES
ELASTICDOCS IN NUMBERS
1M+ PAGES PROCESSED
1,000WELLS
7DISCIPLINES 20
BASINS
GeologyGeophysicsPetrophysicsGeomechanicsReservoir EngineerDrillingProduction
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Addressing the 4Vs of Big Data
Basin
Field
ReservoirWell
Grain
Frame
• Volume • Veracity • Variety • Velocity
High Resolution Basin Insight
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Data
Data
Data
Data
Knowledge Building in
New Ventures
Exploration
Transverse
Management of
Opportunities Secure Knowledge
Sharing
Discovery
P r i v a t e , S e c u r e E x p l o r a t i o n D a t a b a se
C o l l e c t i v e
A w a r e n e s s
Things we learned
o Technology evolution: Cyborg Data + Platform
o Exploration starts at your own (data) backyard
o New ventures can be data-driven, and need not be data-deprived
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NEW EXPLORATION STORY
Allow for easy understanding on:
• Risks associated to seal and migration
• Quality of the reservoir
• Probability of success
• Basin parameters as input to petrophysics, geophysics etc
Clear applications we’ve seen
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Access big data at our fingertips
Cognitive Challenge in Volume
Cognitive ability to digest
Native language
Information criticality
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Alpha
Pack
Scouts
Sole spirits
Visualization of Knowledge Networks
Node = Well
Network Thickness = Strength of Relationship
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Visualization of Knowledge Networks
What this image shows:
• 50 years of drilling history
Intra-relationship among wells
Inter-relationship between basins
Isolation of information – needs lookback?
Successful vs dry wells
Non-existing relationship
Step-out exploration
failures, vintage
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Visualization of Knowledge Networks
Paucity of network
Richness of network
What we can do:
• Add more data
• Add more understanding in areas with network paucity
• Could be opportunities for low-hanging fruits
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What are the wells “gossiping” about
SHARED LOGISTICS
SHARED NEIGHBORS
SHARED RESERVOIRS
SHARED GDE
…Top of the Latrobe level that is shared by the C21A well
…Begin tow from Bellatrix-1 to Calliance-3..
…A comprehensive set of offset wells for Dufresne-1B (includes) Abalone-1
…These wells (250 km & basins apart)… are of paramount importance for the extension of the producing plays discovered in the Paleogene…
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Cognitive Challenge: Language
Auto-machine translate
breaks down language barrier in exploration
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Cognitive Challenge: Language
New feature allows:
❑ Batch translate content in any language
❑ Simultaneous Query & Translate feature allows document to be searched in English, dives thru content in (any) language, and returns answer back in English
Hide OriginalORIGINAL TEXT
Las buenas porosidades y las areniscas limpias
en bloques caracterizan la Formación Plover en
Bodacious-1A. Estas arenas de buena calidad
están entrelazadas con arcilla. No se registraron
muestras significativas de hidrocarburos durante
la perforación de este pozo.
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Cognitive Challenge: Variety• Data Sources
private, internal corporate database
• Formatpdf, excel, word, powerpoint, gis, las, segy
• Disciplinesgeology, geophysics, petrophysics, reservoir engineering, drilling,
production
anydata
databaseML powered
data ingestion Cognitive
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Conclusion
• We started to move from solving analytical (technical) problems to improving (human) cognitive capabilities
• We are moving from machine learning experimentation to focused exploration problem-solving
• Evolving approach to data relationships to software platforms
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Thank you