GeoStreamer Technology:Complete Waveform Imaging (CWI) -

Johan Sverdrup Case Study

J.E.Lie (Lundin), M. Farouki, G. Rnholt, . Korsmo, B. Danielsen, S.Brown, S. Brandsberg-Dahl, A.V. Mavilio, N. Chemingui, D.Whitmore (PGS)

Presented by Rick Irving

2014 HAGI WorkshopBandung, June 23rd 2014

Overview

Survey background

Brief description of CWI technology

Case Study - Johan Sverdrup

Summary & Conclusions

Introduction: Johan Sverdrup Case Study 1st proprietary 3D Dual-Sensor survey, 2009 1600km2 over Luno discovery, North Sea Led to Johan Sverdrup discovery in 2010 - largest oil discovery in last 10 years

Legacy 3D 3D OBC Dual-Sensor 3D

Low relief oil reservoir covering 180 km2 - porous Jurassic sandstone at 1900m Recoverable reserves estimate: 1.7 - 3.3 billion barrels Large uncertainty due to complex shallow section, weathered basement & conglomerates Reprocessed many times by numerous contractors - unable to tie well Accurate depth measurement crucial for estimating reserves and field development Reprocessing using Complete Wavefield Imaging technology

Johan Sverdrup Field

Overview

Survey background

Brief description of CWI technologyhyperTomo - Reflection tomographyFWI - Full waveform InversionSWIM - Separated Wavefield Imaging

Case Study

Summary & Conclusions

Complete Wavefield Imaging (CWI)

The Multiple Benefits of GeoStreamer

hyperTomo using Primary ReflectionsSeparated Wavefield Imaging (SWIM) using Multiples

FWI using Refractions & Diving Waves

GeoStreamer - Dual-Sensor Acquisition

Wavefield Separation Notch DiversityMulti-Sensor streamer technology. Conventional hydrophone-only

streamer.

Vector measurement -incorporates particle velocity.

Scalar measurement -pressure only.

Acquisition solution. Processing solution.

BenefitsBroader bandwidth. Broader bandwidth.

No flat sea assumption.

Insensitive to sea surface & receiver depth variations.

Deterministic Workflow;No multi-dimensional transforms.

No artificial whitening.

4D compliant.

Pre-stack amplitude & phase integrity.Quantitatively accurate AVO/AVA, QI.

Processing & Imaging applications using separated wavefields.

Wavefield Separation

Leveraging wavefields from dual-sensor systemVelocity model building workflow

SEISMIC EVENT WAVEFIELD ALGORITHM APPLICATION

PRIMARY REFLECTIONS UPGOING TOMOGRAPHY Background model for robust FWI

REFRACTIONS RAW HYDROPHONE FWI Hi-res iterative approach for model 0-500m

MULTIPLES UP- & DOWN-GOING SWIM Validation of shallow overburden

PRIMARY REFLECTIONS UPGOING TOMOGRAPHY Hi-res update for deep overburden & target

Wavelet Shift Tomography - hyperTomo

1. Decompose input data into wavelets

2. Migrate wavelets

map from data to model space

3. Estimate 3D residual for each wavelet

data and model space attributes preserved

4. Form equation for each wavelet

5. Invert for velocity update

Beam Migration

RMO

Iterative Tomography

Refines the velocity model byiterative matching of modelled data with recorded data

Refraction-based FWI Driven by refractions and diving

waves Shallow updates Minimum pre-processing,

Reflection-based FWI Designed for use with

backscattered arrivals Allows for deep updates Preprocessing required

- Requires input data with low frequencies- Ideally suited to broad-band seismic data- Provides short wavelength velocity information

Full Waveform Inversion

Etgen & Brandsberg-Dahl: The pseudo-analytical method: Application to acoustic wave propagation. SEG 2009

1-Way WEM is reconfigured to use up-going & down-going wavefields to image the earth with free surface multiple data

Replace S (forward propagated shot - impulse wavelet) with down-going wavefieldReplace R (back-propagated P-total at receivers) with up-going wavefieldApply imaging condition

More extensive illumination of earth; areal wide azimuth source array

S R

Primaries Multiples

Imaging with separated wavefields - SWIM

SWIMsubset

First commercial SWIM applicationLundin Malaysia - PM307

Long et al: Mitigation of the 3D cross-line acquisition footprint using wavefield separation of dual-sensor streamer seismic data.PGCE 2013 Kuala Lumpur

70-90m shallow water

Streamers 12 x 4050m @ 75m

Dual-source, 18.75m spacing

SWIM subset:47 sail lines

427 km = 51,000 shots

Data output:6.25m x 8.75m bins (P-UP)

Limited trial:Migration pursued to 60Hz

No velocity update

No anisotropy investigation

Time slice 120ms Conventional WEM

Time slice 120ms SWIM

PSDM of Primaries - xline

SWIM - xline

Overview

Survey background

Brief description of CWI technology

Case Study:Complete Waveform Imaging (CWI) -Advanced Depth Imaging using Primaries, Multiples & Refractions

Summary & Conclusions

CWI workflow

hyperTomo

FWI

SWIM

hyperTomo

Background model match refracted events in modeled and real data

Iterative approach model down to 600 m below water bottom

SWIM gathers and stack for validation of the shallow overburden

High resolution tomographic update for deep overburden and target

18

Separated Wavefields Imaging (SWIM) -Yields greater illumination from multiples

Full Waveform Inversion (FWI) -Exploits low frequency content from dual-sensor streamer acquisition

CWI - Complete Wavefield ImagingNoise becomes useful

chalk

Reflection tomography - chalk layer updated (model provided by Lundin)

Beam gathers (2012 PSDM model)

chalk

hyperTomo high resolution chalk layer update

Beam gathers (hyperTomo model)

Shot record filtered 3-10hz

Shot record filtered 3-5hz

Low frequencies captured in Dual-Sensor raw hydrophone

Kirchhoff PSDM stack - input to FWI

Kirchhoff PSDM stack - FWI velocity model

channels gas caps

Shaleplug

Kirchhoff PSDM gathers - input model

Kirchhoff PSDM gathers - FWI velocity model

Solving for refraction velocities correspondsto flattening primary reflections

FWI velocity, depth = 240m

FWI velocity, depth = 240m

Channels

Buried pockmarks Shale Plug

Gas

PSDM image and FWI velocity overlay, depth = 240m

FWI velocity, depth = 320m

PSDM image and FWI velocity overlay, depth = 320m

SWIM vs Kirchhoff PSDM

Shallow hazards

High fold

SWIM STACK

KIRCHHOFF PSDM STACK

SWIM 3D view - 250m depth

Seismic - Imaging of multiples

SWIM 3D view with FWI model overlay

Velocity Model from refractions

Comparison SWIM and Kirchhoff at 225m depth slice

Shallow hazards

Resolution of channel

Illumination

KIRCHHOFF PSDM STACK SWIM STACK

SWIM - gathers for velocity model buildingSWIM stack

SWIM common angle gathers

Kirchhoff common offset gathers

PSDM - Input

- Depth mistie- Uncertainty in

estimating reserves;1.7 - 3.3 billion barrels

Impact at target:- Well ties seismic- Oil/Water contact

defined- Confident estimation of

reserves

PSDM - Revised

Robust, high-resolution velocity model in near surface, 0-500m.

Overview

Survey background

Brief description of CWI technology

Case Study:

Summary & Conclusions

Dual-Sensor Acquisition

High resolution velocity model at depth

Kirch WEMBeam RTM

SWIMFWIExploits GeoStreamer low frequencies Exploits near surface illumination

High resolution shallow velocity model

Reflection Tomography

Validation of shallow velocity model

Exploits GeoStreamer S/N

Complete Wavefield Imaging

Wavefield separation

REFRACTIONS MULTIPLES

PRIMARIES

Summary

The dual sensor broadband solution provides:- an acquisition platform for Wavefield Separation- improved S/N reflection data- low frequencies important for FWI- ability to exploit multiples for superior illumination- Complete Wavefield Imaging

Modern imaging technologies are applied to a vintage dual-sensor 3D surveyfor hi-res velocity model building and imaging:

- Independently, shallow small-scale features correlate very well:- velocity model built from refraction FWI- imaging of primaries- imaging of multiples

- Significantly impacts correct structural imaging at target.

Thank you for your attention!