peebles-3d symposium-03 mar 2016

Fast, Actionable and Affordable – making seismic a standard tool for ongoing development operations

Ross Peebles Global Geophysical 03 March 2016

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CEO Perspective on 2016

2016 is a brutal year of great opportunity everything is focused, necessary and meaningful

Objectives:

•  Build a sustainable business

•  Live in the now and plan for the future

•  Gather great people

•  Do interesting and fun work

•  Demonstrate that you can perform and improve

•  Be significant and impactful to your customers

Peebles-GlobalGeophysicalServices-2016

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Innovation and Adoption

What did Ballmer not get?

The iPhone is much, much more than a phone – it is an instant gratification device – fast, easy access to people and information

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Innovation and Adoption

When is Seismic much more than Seismic... When it becomes an “instant gratification tool”, quickly and easily used for every day analysis and decisions

Well Prospectivity & Productivity Analysis-Seismic-based Analytics Ambient Seismic – Fractures and Production - Time Lapse Modular Seismic – A New Acquisition-Processing Approach


Seismic is mostly a mid to long-term planning resource rich, dense data type channeled through specialists and studies – expensive and its takes a long time to go from data collection to actionable information

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–  BriRle/Duc;leQuality–  Differen;alStress–  StressFieldOrienta;on–  Faults&NaturalFractures–  Porosity–  Thickness–  TOC–  Facies–  Oil&WaterSatura;on–  Pressure

Resource / Reservoir Characteristics that drive productivity

Sta9c&DynamicProxiesforProducibility

Canwefindproxiesforthesecharacteris9csinseismica6ributes?

Howdowecapturethecumula0veeffect?

Howdoweincludeengineeringdata?


Well Prospectivity & Productivity Analysis (WPPA) (workflow based on a seismically constrained multivariate analysis)

Multivariate Analysis - a simultaneous statistical analysis of multiple variables (attributes) to predict a known metric

Seismic-based Analytics – Wolfcamp Example

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9Source:LaredoPetroleumInvestorPresenta9on,Apr2015WolfcampExample–PermianBasin

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PredictedProduc9on=34,487;ActualProduc9on=38,430

Source:LaredoPetroleumInvestorPresenta9on,Apr2015

Seismic Attributes 1.AzimuthalAnisotropyproxyforfractures&stress2.KposCurvatureproxyforfractures&faults3.Mu(rigidity)proxyforBri4le/Duc7le4.DominantFrequencyproxyforforma7onthickness

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WPPA - Multivariate Analysis for Operations 3-month Water-Oil Ratio (WOR) – Eagle Ford


3 Month WOR – Stage-level Prediction Comparison of Model to PLT – Eagle Ford (PLT = Production Logging Tool)

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WellDataPLT-WATER

ModelWOR-Water

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Stage16


WPPA - Wolfcamp – University Lands 3D

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*bAAPG Bulletin, v. 89, no. 5 (May 2005), pp. 553–576c*

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•! 356 mi2 of 3D Seismic •! 45 Seismic Attributes •! 46 Wells Production data from 21 wells used for initial modeling Blind test with: •! 8 Vertical Wells •! 17 Horizontal Wells 3 Primary Performance Indicators: •! Curvature (RMS & Kdip) •! 24-28Hz SpecD •! 10-14Hz SpecD

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WPPA - Wolfcamp – University Lands 3D Multivariate Models – 3-month oil per foot

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WPPA - Wolfcamp – University Lands 3D Missed Pay and Refrac Candidates

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WPPA - Wolfcamp – University Lands 3D Identifying Refrac and Sidetrack Candidates

–  BriRle/Duc;leQuality–  Differen;alStress–  StressFieldOrienta;on–  Faults&NaturalFractures–  Porosity–  Thickness–  TOC–  Facies–  Oil&WaterSatura;on–  Pressure

Resource / Reservoir Characteristics that drive productivity

Sta9c&DynamicProxiesforProducibility

Canwefindproxiesforthesecharacteris9csinseismica6ributes?

Howdowecapturethecumula0veeffect?

Howdoweincludeengineeringdata?


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19 Peebles-GlobalGeophysicalServices-2016

Azimuthal Anisotropy with 12-month Cum Gas Production – 79 Eagle Ford Wells – base Eagle Ford

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Azimuthal Anisotropy vs Gas Production

Log-logplot

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thGas

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Short-termproduc9onistheresultofmanyinfluences 20

Log-logplot

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12M

onthGas

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Long-termproduc9onisdrivenbythenaturalfracturenetwork

90-dayCumGas 12-monthCumGas

Ambient Seismic – Before, During, & After

Acous9callyAc9veVolumeDuringProduc9on

AmbientSeismicRecordedDuringS9mula9on

InducedSeismicityVolumeDuringFrac

NaturalSeismicityRevealsAc9veNaturalFractures

AmbientSeismicRecordedMonthsAgerFrac

AmbientSeismicRecordedBeforeFrac

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Ambient Seismic collected during 3D Seismic Acquisition in the Midland Basin Cumulative Semblance Volume & Fracture Images over 8 days

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Ambient Seismic Recorded after Drilling but Before Frac

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Ambient Seismic Recorded during Frac and Twice during Production (Active Production Volume)

Potential Production Volume (PPV) vs

Observed Active Production Volumes (APV)

PPV - (in grey) Imaged 2 months before well was drilled APV - (in blue) Imaged over the first 2.5 years of production

Potential Production Volume

Imaged 2 months before well was

Imaged over the first 2.5 years of

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Ambient Seismic Recorded Before Drilling and During Production

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Ambient Seismic Acquisition

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AutoSeis – Nodal Acquisition

SeismicforPad-basedOpera9ons(drilling,comple;ons,re-comple;ons)

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•  New,innova;ve3Ddesignmakesacquisi;onfastandaffordable–daysratherthanmonthsinthefield

•  Nodalacquisi;onisfastandleavesminimalenvironmentalfootprint–easierpermilng;happierlandowners

•  Acquirebothac;veandambientseismictomaximizetheunderstandingoffaults,fracturesandstressfields

•  Quickdeliveryofhighresolu;onfaultimagesandrockpropertyaRributes–;melyandac;onable


Modular Seismic

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Modular Seismic – Patch Comparison

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Modular Seismic – Time Comparison better data; twice as fast (7 vs 3.6 months)

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ACQUISITION AMBIENT

PROCESSING

INVERSION

ACQUISITION

AMBIENT

PROCESSING

INVERSION

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Summary

•  Productivity is a function of the interplay of many static and dynamic characteristics – natural fractures can be primary

•  Seismic attributes (3D and Ambient) can be proxies for these characteristics

•  You can use seismic to generate predictive 3D models of reservoir properties and production

•  Seismic (3D and Ambient) can be acquired, processed and analyzed in efficient modules at well, pad and large scale

•  Seismic (3D and Ambient) can be applied as a standard operational tool to reduce performance risk, reduce cost and optimize spend and production


Special Thanks to:

•  Tom Fleure, Global Geophysical, Houston

•  Chad Baillie, Global Geophysical, Denver

•  Jan Vermilye, Global Geophysical, Denver

•  Oliver Pfost, Global Geophysical, Houston

•  Laredo Petroleum


peebles-3d symposium-03 mar 2016

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