# SEISMIC INVERSION OVERVIEW

Save this PDF as:

Size: px
Start display at page:

## Transcription

1 DHI CONSORTIUM SEISMIC INVERSION OVERVIEW Rocky Roden September 2011

2 NOTE: Terminology for inversion varies, depending on the different contractors and service providers, emphasis on certain approaches, and the goals to be accomplished. There are numerous combinations, hybrids, and variations of these inversion methods. This overview attempts to summarize the most common terminology and inversion approaches described in the industry.

3 Seismic Inversion Outline Inversion Definition and Terms Required Data Types of Seismic Inversion Role of Inversion Realistic Expectation from Inversion Inversion and New SEC Regulations

4 What is Inversion? Inversion transforms seismic reflection data into rock and fluid properties. The objective of seismic inversion is to convert reflectivity data (interface properties) to layer properties. To determine elastic parameters, the reflectivity from AVO effects must be inverted. The most basic inversion calculates acoustic impedance (density X velocity) of layers from which predictions about lithology and porosity can be made. The more advanced inversion methods attempt to discriminate specifically between lithology, porosity, and fluid effects. Inversions can be grouped into categories: pre-stack vs. post-stack, deterministic vs. geostatistical, or relative vs. absolute. Inversion is the flip side of forward modeling.

5 Common Inversion Terms Relative Impedance Relative changes in inversion, not real values. Absolute Impedance Actual acoustic impedance, contains low frequency trend. Deterministic Inversion A single output value is determined from the input. Stochastic (Probabilistic) Inversion A range of equally probable outputs are derived from the input (under controlled number of inputs). Objective Function A quantitative measure of the misfit between the observed data and the data predicted by inversion (L1 and L2 Norm). L2 Norm Most common measure of data misfit, a least squares difference (sum of the square of the data residuals). L1 Norm Misfit measure that is the sum of the absolute data residuals. Global More than one trace is inverted at the same time within a common objective function. The number of traces inverted at once depends on the algorithm. Simulated Annealing A global optimization technique based on crystal growth in a cooling volcanic melt. Computes difference between seismic and convolutional model with applied wavelet. The model is perturbed and a new model is simulated, and the difference is again measured. Differences are compared with the smallest difference accepted and the other differences accepted with a probability (Metropolis Criterion). The process is repeated until and there is a very small residual or a threshold has been reached.

6 Forward Modeling takes well logs, combines with wavelet to produce synthetic seismic trace Inversion takes seismic trace, removes effects of estimated wavelet and creates acoustic impedance values Oilfield Review, 2008

7 Data Considerations for Inversion Pre-stack and/or post-stack time migrated seismic data Well data conditioning and editing is necessary Wavelet estimation required for all modern inversion approaches -Deterministic -Statistical Low Frequency Trend absolute acoustic impedance contains a low frequency trend that must be obtained usually from well control or stacking velocities NOTE: Without wavelet estimation and well calibration, the inversion solution is non-unique.

8 Data Considerations for Inversion Pillar, 2011

9 Data Considerations for Inversion Low Frequency Trend in Red Oilfield Review, 2008

10 Data Considerations for Inversion Missing low frequencies and their modeling from well log data cause bias in inversion, regardless of the methodology. Determining low frequency issues: Lithologies encountered at the wells thin or thicken away from the wells. In fact, some lens-like possible plays between wells are often difficult or impossible to model accurately. Lateral geological changes away from the wells have no resemblance to the geological layers at wells used fro low frequency model generation, e.g., sand injections. There are excessive lateral changes in rock and reservoir properties (e.g., porosity changes and shaling out). Ozdemir, 2009

11 Data Considerations for Inversion Rock physics approach to well log preparation for inversion: Continuous reconstruction of formation properties along the wellbore, both for reservoirs and non-reservoirs Characterization of rocks in terms of their elastic properties Establishment of causal relationships between elastic and petrophysical properties such as porosity, clay content and fluid saturation NOTE: Depends on inversion approach and stage of exploration through development cycle.

12 Types of Inversion Running Sum Inversion like (Runsum) Recursive Trace integration (relative acoustic impedance) Colored Inversion Sparse Spike (CSSI) Model-Based Inversion AVO Inversion Elastic Impedance Extended Elastic Impedance Simultaneous Inversion Stochastic Inversion Geostatistical Bayesian

13 Running Sum Running Sum is the integration or adding of seismic amplitudes on a seismic trace. It is the cumulative sum of amplitude values at any time sample starting from the top to the end of the trace. Running Sum provides an approximation to acoustic impedance (velocity X density), while lacking the low frequency trend of a full inversion this can be useful over short intervals. The less noise and the broader the bandwidth (narrower the wavelet), the better will be the approximation to impedance.

14 Running Sum Normal Amplitude Running Sum Courtesy SMT

15 Recursive Trace Integration Recursive/Trace Integration (RTI) employs the discrete recursive inversion formula (below) which indicates that the acoustic impedance of a particular layer and the reflection coefficient at its base can be used to calculate the acoustic impedance of the next layer. An estimate of the acoustic impedance of the first layer is required. Normal incidence reflectivity Recursive inversion formula r = reflection coefficient Z = impedance

16 Recursive Trace Integration Seismic section from Alberta highlighting an anomalous bright spot zone. Recursive inversion of the section above Russell and Hampson, 2006

17 Colored Inversion Colored Inversion transforms migrated seismic data into a bandlimited acoustic impedance volume by shaping the mean seismic spectrum into the impedance log spectrum. This approach only gives a relative acoustic impedance which does not contain any low frequency components. This inversion method can make it simpler to interpret the variations in thickness related to various lithologic packages, properties of thin beds, and changes in acoustic impedance associated with fluid effects and rock property variations. Veeken and Da Silva, 2004

18 Colored Inversion Colored Inversion was first introduced by Lancaster and Whitcombe (2000) and involves deriving an operator that transforms the seismic amplitude spectrum to the acoustic impedance spectrum from well logs with a -90 phase change. This typically requires crossplotting the log of the well acoustic impedances versus log of amplitudes to derive a best-fit line to the data. The slope of this line is used to develop an operator to apply to the seismic data to convert to acoustic impedance. The logic employed is that the gross spectral properties from the well acoustic impedances in any given field are reasonably constant. A phase rotation may be applied to the seismic data, but this approach assumes the seismic is zero phase. Colored inversion may establish a base case to compare against more sophisticated inversion techniques Courtesy SMT

19 Colored Inversion Conventional Seismic Line Colored Inversion Colored Inversion Colored Inversion Courtesy SMT

20 Sparse Spike Inversion Sparse Spike Inversion assumes that seismic reflectivity is a series of large spikes embedded in a background of small spikes (assumes only large spikes are meaningful). This approach seeks the simplest possible reflectivity model of spikes, that when convolved with the wavelet produces a synthetic that matches the real data. Non-linear Sparse Spike Inversion (Constrained Sparse Spike Inversion-CSSI) employs an optimization loop where the wavelet is updated (non-linearly) so that the mis-match between the synthetic and real seismic is minimized.

21 Sparse Spike Inversion Saxena and Bhatnagar, 2008

22 Model-Based Inversion Model-Based Inversion typically starts with a low frequency model of the P-impedance and then the model is perturbed until a good fit is obtained between the seismic data and a synthetic trace using the recursive formula. The Generalized Linear Inversion (GLI) method perturbs an initial acoustic impedance estimate and determines the differences between the synthetic trace and the real data (simulated annealing and least square fits are often applied). Principal Component Analysis (PCA) method computes a standard response from which the input can be generated by applying specific weighting factors determined from well control (linear interpolation). The results of the convolution with the seismic wavelet are compared with the seismic traces and the velocity and density models are perturbed to reduce the discrepancy.

23 Model-Based Inversion Veeken and Da Silva, 2004

24 Model-Based Inversion Wavelet Initial Model Seismic Data Synthetic Data Misfit Function Stochastic Model Update No Optimisation by Simulated Annealing Convergent? Yes Model Based Inversion Utilizing Simulating Annealing Stop Courtesy Equipoise

25 Model-Based Inversion Seismic section from Alberta highlighting an anomalous bright spot zone. Model based inversion of the section above Russell and Hampson, 2006

26 AVO Elastic Impedance Connolly (1999) developed an angle dependent analogy to acoustic impedance to account for AVO effects. Elastic impedance is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Input for elastic impedance is some form of angle stack (e.g., near, mid, and far). Wavelets are determined for each offset angle volume. This approach is accurate for small to moderate impedance changes.

27 AVO Elastic Impedance Connolly relates the Aki-Richards (Shuey) linear Zoeppritz approximation: to an elastic impedance relationship: Combining the two expressions gives elastic impedance: Variations of this approach include using the Shuey two-term approximation (good to ), assume Vp/Vs=2 or Vs calculation, and Extended Elastic Impedance (Whitcombe et al., 2002)

28 AVO Elastic Impedance Veeken and Da Silva, 2004

29 AVO Elastic Impedance Elastic impedance displays for different offset angles Veeken and Da Silva, 2004

30 AVO Extended Elastic Impedance Whitcombe et al (2002) describes an approach that extends beyond a typical incident angle range of 0 to 30 for seismic data to -90 to +90. The sin²ɵ term in the Shuey 2-term Zoeppritz linear approximation limits the range at which reflectivities can be defined. If this approximation is re-written as R = A + Btanx then scaled by cosx then a scaled reflectivity equation can be written: R = A cosx + B sinx. Extended Elastic Impedance logs can be generated from P-wave, S- wave, and density logs for each angle x. Once x is known then equivalent seismic sections can be generated.

31 AVO Extended Elastic Impedance EEI logs at different angles: Compressional modulus = +12 Lame s parameter = =20 Shear impedance = -50 Vp/Vs = +45 Acoustic impedance = 0 Francis and Hicks, 2006

32 AVO Extended Elastic Impedance Connolly, 2010

33 AVO Extended Elastic Impedance Connolly, 2010

34 AVO Extended Elastic Impedance Francis and Hicks, 2006

35 AVO Simultaneous Inversion Simultaneous inversion is a prestack inversion method that uses multiple offset or angle stacks. This method solves for S impedance, P impedance, and density, which are key for descriminating lithology, porosity, and fluid effects. For each input partial stack a wavelet is estimated. All models, partial stacks, and wavelets are input into a single inversion algorithm and solved simultaneously compensating for offset dependent phase, bandwidth, tuning and NMO stretch effects.

36 AVO Simultaneous Inversion NMO Gather (Full Offset) Wavelets Macro-models Simultaneous Inversion Constrained Model-driven Global (SA) P-wave Impedance Model S-wave Impedance Model Simultaneous Inversion Workflow Courtesy Equipoise

37 AVO Simultaneous Inversion Russell and Hampson, 2006 Simultaneous P-Impedance Inversion

38 AVO Simultaneous Inversion Simultaneous P-Impedance Inversion Vp/Vs ratio from dividing P and S-impedance sections from simultaneous inversion Russell and Hampson, 2006

39 Predicting Other Rock Properties from Pre-Stack Inversion Pre-stack Inversion Vp/Vs Poisson s Ratio Acoustic (Ip) Impedance Shear (Is) Impedance Elastic Impedance EI Lamé Parameter Lamé Parameter Lithology Fluid Content Porosity Pore Pressure Lamé Parameter Courtesy Equipoise

40 Pre-Stack Inversion allows discriminating lithologies and fluids Bunch and Dromgoole, 1995 Pillar, 2011

41 AVO Elastic Impedance Reservoir attributes from Elastic Impedance Inversion Veeken and Da Silva, 2004

42 Elastic Impedance Simultaneous Inversion Rasmussen et al., 2004

43 Elastic Impedance-Simultaneous Inversion Poisson s Ratio From Elastic Impedance Inversion From Simultaneous Inversion Saxena and Bhatnagar, 2008

44 Stochastic Inversion - Geostatistical Geostatistical or probabilistic inversion uses quantification of uncertainties attached to the inversion input data. Probability density functions (PDF) are defined and an earth model is simulated, which is perturbed to minimize the discrepancy between the modeled and measured seismic data (simulated annealing) producing multiple realizations. The PDF determination comes from well logs, spatial properties (variograms) and lithological distributions. It is critical that the interpreter quantify the uncertainties in a realistic way, especially in the absence or minimal well control in specific areas.

45 Stochastic Inversion - Geostatistical The workflow for performing a geostatistical inversion showing the input data and the outputted model realizations. McCrank et al., 2009

46 Stochastic Inversion - Geostatistical The acoustic impedance inversion results with the mean acoustic impedance results of the multiple realizations in the upper left. McCrank et al., 2009

47 Stochastic Inversion - Bayesian Seismic inversion that uses Baye s rule allows the information from all available measurements to be integrated into a consistent image of the reservoir and constrain these solutions based on a priori knowledge about the subsurface parameters. Prior knowledge about the model parameters usually is combined with a likelihood function, which depends on the misfit between the model response and the observed seismic data

48 Stochastic Inversion - Bayesian Pillar, 2011

49 Stochastic Inversion - Bayesian Pillar, 2011

50 Categories of Seismic Inversion Running Sum Well Control Post Stack Pre Stack Relative Imp. Absolute Imp. Deterministic Probabilistic Recursive Trace Integration Colored Inversion Sparse Spike (CSSI) Model Based Inversion Elastic Impedance Simultaneous Inversion Geostatistical Inversion Bayesian Inversion

51 Applicable Inversions for Exploration through Development Running Sum Exploration Exploitation Development Recursive Trace Integration Colored Inversion Sparse Spike (CSSI) Model Based Inversion Elastic Impedance Simultaneous Inversion Geostatistical Inversion Bayesian Inversion

52 A Few Additional Types of Inversion Simultaneous geostatistical partial stack inversion Spectral inversion Pre-stack waveform inversion Multi-component inversion Multi-azimuth inversion Inversion incorporating EM and FTG data 3D Full Waveform Inversion

53 Seismic Inversion Checklist (modified from Ikon website) 1. Check log data and edit accordingly. 2. Perform rock physics analysis to determine if inversion is useful. 3. Check seismic data for proper processing and conditioning, S/N, accurate partial stacks, etc. 4. Well ties and low frequency background model: -Do you get credible wavelets? -Are wavelets consistent across wells? -Is a broadband inversion required? 5. Be sure and employ appropriate inversion algorithm. 6. QC is paramount: -Check all wells and match of wavelets. -From impedances forward model to synthetic seismic; compare with actual seismic. -Does it make geological sense? -Is low frequency trend applied correctly? 7. Use impedance results intelligently they are not the end goal!

54 SEC Regulations and Inversion Pillar, 2011

55 SEC Regulations and Inversion Oil and gas companies may use any "reliable technology" to establish reserves volumes in addition to those established by production and flow test data. Oil and gas companies may classify proved undeveloped reserves ("PUDs") any distance from known proved reserves (rather than only in immediately offsetting units) based on a reasonable certainty standard. Use of reliable technology: A registrant is required to disclose, in general terms, the technologies used in ascertaining the reasonable certainty of the PUD locations producing hydrocarbons. Any technology stated must be field tested to demonstrate consistency and repeatability. In reviewing disclosures of the technologies used, some very simple statements that a combination of these technologies was used were noted: analogy, 2-D and 3-D seismic data, volumetric and material balance analysis, decline curves, petrophysics, and log analysis. A company does not need to disclose proprietary technologies or the mix of proprietary methods.

56 Conclusions 1) Seismic Inversion is not a unique process. 2) Seismic and well log information should be optimally conditioned for reliable inversion results. 3) There is a trade-off between work involved/cost/time and quality of the final inversion. 4) A rock physics study can help determine what the end product from inversion should be and whether this is attainable with the existing data. 5) Even when advanced inversion algorithms are chosen, a simpler deterministic inversion perhaps should be run for feasibility and as a yardstick of what can be resolved. 6) Most seismic inversion workflows are not linear and require reasonable inputs and usually numerous iterations. 7) Will the SEC accept inversion results for booking reserves?

57 Indeed, given that we can now directly invert to the acoustic properties using simultaneous inversion, some workers hold the view that conventional two-term AVO techniques are now passé. This is naïve given that deriving an accurate estimate of Poisson ratio from seismic is actually quite difficult, requiring a stringent set of data conditions. In many cases, bias of one form or another is introduced into the result, for example when merging the low frequency component. The interpreter needs to understand both conventional AVO approaches as well as the latest trends in inversion. Rob Simm What makes the wiggle waggle: a perspective on rock physics, First Break, June 2011

58 DHI CONSORTIUM Thank You

### 23855 Rock Physics Constraints on Seismic Inversion

23855 Rock Physics Constraints on Seismic Inversion M. Sams* (Ikon Science Ltd) & D. Saussus (Ikon Science) SUMMARY Seismic data are bandlimited, offset limited and noisy. Consequently interpretation of

### QUANTITATIVE INTERPRETATION

QUANTITATIVE INTERPRETATION THE AIM OF QUANTITATIVE INTERPRETATION (QI) IS, THROUGH THE USE OF AMPLITUDE ANALYSIS, TO PREDICT LITHOLOGY AND FLUID CONTENT AWAY FROM THE WELL BORE This process should make

### Stochastic vs Deterministic Pre-stack Inversion Methods. Brian Russell

Stochastic vs Deterministic Pre-stack Inversion Methods Brian Russell Introduction Seismic reservoir analysis techniques utilize the fact that seismic amplitudes contain information about the geological

### An overview of AVO and inversion

P-486 An overview of AVO and inversion Brian Russell, Hampson-Russell, CGGVeritas Company Summary The Amplitude Variations with Offset (AVO) technique has grown to include a multitude of sub-techniques,

### Quantitative Interpretation

Quantitative Interpretation The aim of quantitative interpretation (QI) is, through the use of amplitude analysis, to predict lithology and fluid content away from the well bore. This process should make

### Reservoir Characterization using AVO and Seismic Inversion Techniques

P-205 Reservoir Characterization using AVO and Summary *Abhinav Kumar Dubey, IIT Kharagpur Reservoir characterization is one of the most important components of seismic data interpretation. Conventional

### Estimation of density from seismic data without long offsets a novel approach.

Estimation of density from seismic data without long offsets a novel approach. Ritesh Kumar Sharma* and Satinder Chopra Arcis seismic solutions, TGS, Calgary Summary Estimation of density plays an important

### New Frontier Advanced Multiclient Data Offshore Uruguay. Advanced data interpretation to empower your decision making in the upcoming bid round

New Frontier Advanced Multiclient Data Offshore Uruguay Advanced data interpretation to empower your decision making in the upcoming bid round Multiclient data interpretation provides key deliverables

### Rock Physics and Quantitative Wavelet Estimation. for Seismic Interpretation: Tertiary North Sea. R.W.Simm 1, S.Xu 2 and R.E.

Rock Physics and Quantitative Wavelet Estimation for Seismic Interpretation: Tertiary North Sea R.W.Simm 1, S.Xu 2 and R.E.White 2 1. Enterprise Oil plc, Grand Buildings, Trafalgar Square, London WC2N

### Pre-Stack Seismic Inversion and Amplitude Versus Angle Modeling Reduces the Risk in Hydrocarbon Prospect Evaluation

Advances in Petroleum Exploration and Development Vol. 7, No. 2, 2014, pp. 30-39 DOI:10.3968/5170 ISSN 1925-542X [Print] ISSN 1925-5438 [Online] www.cscanada.net www.cscanada.org Pre-Stack Seismic Inversion

### AFI (AVO Fluid Inversion)

AFI (AVO Fluid Inversion) Uncertainty in AVO: How can we measure it? Dan Hampson, Brian Russell Hampson-Russell Software, Calgary Last Updated: April 2005 Authors: Dan Hampson, Brian Russell 1 Overview

Multi-scenario, multi-realization seismic inversion for probabilistic seismic reservoir characterization Kester Waters* and Michael Kemper, Ikon Science Ltd. Summary We propose a two tiered inversion strategy

### A031 Porosity and Shale Volume Estimation for the Ardmore Field Using Extended Elastic Impedance

A31 Porosity and Shale Volume Estimation for the Ardmore Field Using Extended Elastic Impedance A.M. Francis* (Earthworks Environment & Resources Ltd) & G.J. Hicks (Earthworks Environment & Resources Ltd)

### Lithology prediction and fluid discrimination in Block A6 offshore Myanmar

10 th Biennial International Conference & Exposition P 141 Lithology prediction and fluid discrimination in Block A6 offshore Myanmar Hanumantha Rao. Y *, Loic Michel, Hampson-Russell, Kyaw Myint, Ko Ko,

### Statistical Rock Physics

Statistical - Introduction Book review 3.1-3.3 Min Sun March. 13, 2009 Outline. What is Statistical. Why we need Statistical. How Statistical works Statistical Rock physics Information theory Statistics

### Comparative Study of AVO attributes for Reservoir Facies Discrimination and Porosity Prediction

5th Conference & Exposition on Petroleum Geophysics, Hyderabad-004, India PP 498-50 Comparative Study of AVO attributes for Reservoir Facies Discrimination and Porosity Prediction Y. Hanumantha Rao & A.K.

### Simultaneous Inversion of Clastic Zubair Reservoir: Case Study from Sabiriyah Field, North Kuwait

Simultaneous Inversion of Clastic Zubair Reservoir: Case Study from Sabiriyah Field, North Kuwait Osman Khaled, Yousef Al-Zuabi, Hameed Shereef Summary The zone under study is Zubair formation of Cretaceous

### Introduction: Simultaneous AVO Inversion:

Implementation of AVO, AVOAz Inversion and Ant Tracking Techniques in Wembley Valhalla Integrated Merge 3D Seismic Survey, Alberta Homayoun Gerami, Patty Evans WesternGeco Introduction: The Wembley Valhalla

### An Integrated Workflow for Seismic Data Conditioning and Modern Prestack Inversion Applied to the Odin Field. P.E.Harris, O.I.Frette, W.T.

An Integrated Workflow for Seismic Data Conditioning and Modern Prestack Inversion Applied to the Odin Field P.E.Harris, O.I.Frette, W.T.Shea Talk Outline Introduction Motivation Introducing Pcube+ Gather

### Reservoir connectivity uncertainty from stochastic seismic inversion Rémi Moyen* and Philippe M. Doyen (CGGVeritas)

Rémi Moyen* and Philippe M. Doyen (CGGVeritas) Summary Static reservoir connectivity analysis is sometimes based on 3D facies or geobody models defined by combining well data and inverted seismic impedances.

### Pre-stack (AVO) and post-stack inversion of the Hussar low frequency seismic data

Pre-stack (AVO) and post-stack inversion of the Hussar low frequency seismic data A.Nassir Saeed, Gary F. Margrave and Laurence R. Lines ABSTRACT Post-stack and pre-stack (AVO) inversion were performed

### RC 2.7. Main Menu. SEG/Houston 2005 Annual Meeting 1355

Thierry Coléou, Fabien Allo and Raphaël Bornard, CGG; Jeff Hamman and Don Caldwell, Marathon Oil Summary We present a seismic inversion method driven by a petroelastic model, providing fine-scale geological

### Integration of Rock Physics Models in a Geostatistical Seismic Inversion for Reservoir Rock Properties

Integration of Rock Physics Models in a Geostatistical Seismic Inversion for Reservoir Rock Properties Amaro C. 1 Abstract: The main goal of reservoir modeling and characterization is the inference of

### Sensitivity Analysis of Pre stack Seismic Inversion on Facies Classification using Statistical Rock Physics

Sensitivity Analysis of Pre stack Seismic Inversion on Facies Classification using Statistical Rock Physics Peipei Li 1 and Tapan Mukerji 1,2 1 Department of Energy Resources Engineering 2 Department of

### Seismic characterization of Montney shale formation using Passey s approach

Seismic characterization of Montney shale formation using Passey s approach Ritesh Kumar Sharma*, Satinder Chopra and Amit Kumar Ray Arcis Seismic Solutions, Calgary Summary Seismic characterization of

### Elastic impedance inversion from robust regression method

Elastic impedance inversion from robust regression method Charles Prisca Samba 1, Liu Jiangping 1 1 Institute of Geophysics and Geomatics,China University of Geosciences, Wuhan, 430074 Hubei, PR China

Geostatistical Reservoir Characterization of Deepwater Channel, Offshore Malaysia Trisakti Kurniawan* and Jahan Zeb, Petronas Carigali Sdn Bhd, Jimmy Ting and Lee Chung Shen, CGG Summary A quantitative

### Recent advances in application of AVO to carbonate reservoirs: case histories

Recent advances in application of AVO to reservoirs: case histories Yongyi Li, Bill Goodway*, and Jonathan Downton Core Lab Reservoir Technologies Division *EnCana Corporation Summary The application of

Reservoir properties estimation from marine broadband seismic without a-priori well information: A powerful de-risking workflow Cyrille Reiser*, Matt Whaley and Tim Bird, PGS Reservoir Limited Summary

### Net-to-gross from Seismic P and S Impedances: Estimation and Uncertainty Analysis using Bayesian Statistics

Net-to-gross from Seismic P and S Impedances: Estimation and Uncertainty Analysis using Bayesian Statistics Summary Madhumita Sengupta*, Ran Bachrach, Niranjan Banik, esterngeco. Net-to-gross (N/G ) is

### SEG/San Antonio 2007 Annual Meeting. Summary

A comparison of porosity estimates obtained using post-, partial-, and prestack seismic inversion methods: Marco Polo Field, Gulf of Mexico. G. Russell Young* and Mrinal K. Sen, The Institute for Geophysics

### Multiple Scenario Inversion of Reflection Seismic Prestack Data

Downloaded from orbit.dtu.dk on: Nov 28, 2018 Multiple Scenario Inversion of Reflection Seismic Prestack Data Hansen, Thomas Mejer; Cordua, Knud Skou; Mosegaard, Klaus Publication date: 2013 Document Version

### A Petroleum Geologist's Guide to Seismic Reflection

A Petroleum Geologist's Guide to Seismic Reflection William Ashcroft WILEY-BLACKWELL A John Wiley & Sons, Ltd., Publication Contents Preface Acknowledgements xi xiii Part I Basic topics and 2D interpretation

### Towards Interactive QI Workflows Laurie Weston Bellman*

Laurie Weston Bellman* Summary Quantitative interpretation (QI) is an analysis approach that is widely applied (Aki and Richards, 1980, Verm and Hilterman, 1995, Avseth et al., 2005, Weston Bellman and

### We apply a rock physics analysis to well log data from the North-East Gulf of Mexico

Rock Physics for Fluid and Porosity Mapping in NE GoM JACK DVORKIN, Stanford University and Rock Solid Images TIM FASNACHT, Anadarko Petroleum Corporation RICHARD UDEN, MAGGIE SMITH, NAUM DERZHI, AND JOEL

### HampsonRussell. A comprehensive suite of reservoir characterization tools. cgg.com/geosoftware

HampsonRussell A comprehensive suite of reservoir characterization tools cgg.com/geosoftware HampsonRussell Software World-class geophysical interpretation HampsonRussell Software is a comprehensive suite

### Thomas Bayes versus the wedge model: An example inference using a geostatistical prior function

Thomas Bayes versus the wedge model: An example inference using a geostatistical prior function Jason M. McCrank, Gary F. Margrave, and Don C. Lawton ABSTRACT The Bayesian inference is used to estimate

### Deterministic and stochastic inversion techniques used to predict porosity: A case study from F3-Block

Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master's Theses and Master's Reports 2015 Deterministic and stochastic inversion techniques used to predict porosity: A

### SEG Houston 2009 International Exposition and Annual Meeting. that the project results can correctly interpreted.

Calibration of Pre-Stack Simultaneous Impedance Inversion using Rock Physics Scott Singleton and Rob Keirstead, Rock Solid Images Log Conditioning and Rock Physics Modeling Summary Geophysical Well Log

### Quantitative interpretation using inverse rock-physics modeling on AVO data

Quantitative interpretation using inverse rock-physics modeling on AVO data Erling Hugo Jensen 1, Tor Arne Johansen 2, 3, 4, Per Avseth 5, 6, and Kenneth Bredesen 2, 7 Downloaded 08/16/16 to 129.177.32.62.

Ehsan Zabihi Naeini*, Ikon Science & Russell Exley, Summit Exploration & Production Ltd Summary Quantitative interpretation (QI) is an important part of successful Central North Sea exploration, appraisal

### THE USE OF SEISMIC ATTRIBUTES AND SPECTRAL DECOMPOSITION TO SUPPORT THE DRILLING PLAN OF THE URACOA-BOMBAL FIELDS

THE USE OF SEISMIC ATTRIBUTES AND SPECTRAL DECOMPOSITION TO SUPPORT THE DRILLING PLAN OF THE URACOA-BOMBAL FIELDS Cuesta, Julián* 1, Pérez, Richard 1 ; Hernández, Freddy 1 ; Carrasquel, Williams 1 ; Cabrera,

### P191 Bayesian Linearized AVAZ Inversion in HTI Fractured Media

P9 Bayesian Linearized AAZ Inversion in HI Fractured Media L. Zhao* (University of Houston), J. Geng (ongji University), D. Han (University of Houston) & M. Nasser (Maersk Oil Houston Inc.) SUMMARY A new

### Impact of Phase Variations on Quantitative AVO Analysis

Impact of Phase Variations on Quantitative AVO Analysis Summary A.K. Srivastava, V. Singh*, D.N. Tiwary and V. Rangachari GEOPIC, ONGC, Dehradun Email: ak_sri3@rediffmail.com Effectiveness of AVO techniques

### Rock physics integration of CSEM and seismic data: a case study based on the Luva gas field.

Rock physics integration of CSEM and seismic data: a case study based on the Luva gas field. Peter Harris*, Zhijun Du, Harald H. Soleng, Lucy M. MacGregor, Wiebke Olsen, OHM-Rock Solid Images Summary It

### Edinburgh Anisotropy Project, British Geological Survey, Murchison House, West Mains

Frequency-dependent AVO attribute: theory and example Xiaoyang Wu, 1* Mark Chapman 1,2 and Xiang-Yang Li 1 1 Edinburgh Anisotropy Project, British Geological Survey, Murchison House, West Mains Road, Edinburgh

### Reservoir properties inversion from AVO attributes

Reservoir properties inversion from AVO attributes Xin-gang Chi* and De-hua Han, University of Houston Summary A new rock physics model based inversion method is put forward where the shaly-sand mixture

### The Marrying of Petrophysics with Geophysics Results in a Powerful Tool for Independents Roger A. Young, eseis, Inc.

The Marrying of Petrophysics with Geophysics Results in a Powerful Tool for Independents Roger A. Young, eseis, Inc. While the application of new geophysical and petrophysical technology separately can

### Seismic reservoir characterization in offshore Nile Delta.

Seismic reservoir characterization in offshore Nile Delta. Part II: Probabilistic petrophysical-seismic inversion M. Aleardi 1, F. Ciabarri 2, B. Garcea 2, A. Mazzotti 1 1 Earth Sciences Department, University

### A021 Petrophysical Seismic Inversion for Porosity and 4D Calibration on the Troll Field

A021 Petrophysical Seismic Inversion for Porosity and 4D Calibration on the Troll Field T. Coleou* (CGG), A.J. van Wijngaarden (Hydro), A. Norenes Haaland (Hydro), P. Moliere (Hydro), R. Ona (Hydro) &

### The progressive role of Quantitative Seismic Interpretation Unlocking subsurface opportunities From qualitative to quantitative

The progressive role of Quantitative Seismic Interpretation Unlocking subsurface opportunities From qualitative to quantitative Bruno de Ribet, Technology Global Director Peter Wang, Technical Sales Advisor

### RC 1.3. SEG/Houston 2005 Annual Meeting 1307

from seismic AVO Xin-Gong Li,University of Houston and IntSeis Inc, De-Hua Han, and Jiajin Liu, University of Houston Donn McGuire, Anadarko Petroleum Corp Summary A new inversion method is tested to directly

### Integrating rock physics modeling, prestack inversion and Bayesian classification. Brian Russell

Integrating rock physics modeling, prestack inversion and Bayesian classification Brian Russell Introduction Today, most geoscientists have an array of tools available to perform seismic reservoir characterization.

### An empirical method for estimation of anisotropic parameters in clastic rocks

An empirical method for estimation of anisotropic parameters in clastic rocks YONGYI LI, Paradigm Geophysical, Calgary, Alberta, Canada Clastic sediments, particularly shale, exhibit transverse isotropic

### SeisLink Velocity. Key Technologies. Time-to-Depth Conversion

Velocity Calibrated Seismic Imaging and Interpretation Accurate Solution for Prospect Depth, Size & Geometry Accurate Time-to-Depth Conversion was founded to provide geologically feasible solutions for

### SEG/New Orleans 2006 Annual Meeting

Carmen C. Dumitrescu, Sensor Geophysical Ltd., and Fred Mayer*, Devon Canada Corporation Summary This paper provides a case study of a 3D seismic survey in the Leland area of the Deep Basin of Alberta,

### Amplitude variation with offset AVO. and. Direct Hydrocarbon Indicators DHI. Reflection at vertical incidence. Reflection at oblique incidence

Amplitude variation with offset AVO and Direct Hydrocarbon Indicators DHI Reflection at vertical incidence Reflection coefficient R(p) c α 1 S wavespeed β 1 density ρ 1 α 2 S wavespeed β 2 density ρ 2

### Fifteenth International Congress of the Brazilian Geophysical Society. Copyright 2017, SBGf - Sociedade Brasileira de Geofísica

Geostatistical Reservoir Characterization in Barracuda Field, Campos Basin: A case study Frank Pereira (CGG)*, Ted Holden (CGG), Mohammed Ibrahim (CGG) and Eduardo Porto (CGG). Copyright 2017, SBGf - Sociedade

### A seismic reservoir characterization and porosity estimation workflow to support geological model update: pre-salt reservoir case study, Brazil

A seismic reservoir characterization and porosity estimation workflow to support geological model update: pre-salt reservoir case study, Brazil Laryssa Oliveira 1*, Francis Pimentel 2, Manuel Peiro 1,

### Workflows for Sweet Spots Identification in Shale Plays Using Seismic Inversion and Well Logs

Workflows for Sweet Spots Identification in Shale Plays Using Seismic Inversion and Well Logs Yexin Liu*, SoftMirrors Ltd., Calgary, Alberta, Canada yexinliu@softmirrors.com Summary Worldwide interest

### Post-stack inversion of the Hussar low frequency seismic data

Inversion of the Hussar low frequency seismic data Post-stack inversion of the Hussar low frequency seismic data Patricia E. Gavotti, Don C. Lawton, Gary F. Margrave and J. Helen Isaac ABSTRACT The Hussar

### Practical aspects of AVO modeling

Practical aspects of AVO modeling YONGYI LI, Paradigm Geophysical, Calgary, Canada JONATHAN DOWNTON, Veritas, Calgary, Canada, YONG XU, Arcis Corporation, Calgary, Canada AVO (amplitude variation with

### URTeC: Summary

URTeC: 2665754 Using Seismic Inversion to Predict Geomechanical Well Behavior: a Case Study From the Permian Basin Simon S. Payne*, Ikon Science; Jeremy Meyer*, Ikon Science Copyright 2017, Unconventional

### Integrating reservoir flow simulation with time-lapse seismic inversion in a heavy oil case study

Integrating reservoir flow simulation with time-lapse seismic inversion in a heavy oil case study Naimeh Riazi*, Larry Lines*, and Brian Russell** Department of Geoscience, University of Calgary **Hampson-Russell

### Use of Seismic Inversion Attributes In Field Development Planning

IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) e-issn: 2321 0990, p-issn: 2321 0982.Volume 6, Issue 2 Ver. II (Mar. Apr. 2018), PP 86-92 www.iosrjournals.org Use of Seismic Inversion Attributes

Facies modeling in unconventional reservoirs using seismic derived facies probabilities Reinaldo J. Michelena*, Omar G. Angola, and Kevin S. Godbey, ireservoir.com, Inc. Summary We present in this paper

### Toward an Integrated and Realistic Interpretation of Continuous 4D Seismic Data for a CO 2 EOR and Sequestration Project

SPE-183789-MS Toward an Integrated and Realistic Interpretation of Continuous 4D Seismic Data for a CO 2 EOR and Sequestration Project Philippe Nivlet, Robert Smith, Michael A. Jervis, and Andrey Bakulin,

### Bayesian Lithology-Fluid Prediction and Simulation based. on a Markov Chain Prior Model

Bayesian Lithology-Fluid Prediction and Simulation based on a Markov Chain Prior Model Anne Louise Larsen Formerly Norwegian University of Science and Technology, N-7491 Trondheim, Norway; presently Schlumberger

### An empirical study of hydrocarbon indicators

An empirical study of hydrocarbon indicators Brian Russell 1, Hong Feng, and John Bancroft An empirical study of hydrocarbon indicators 1 Hampson-Russell, A CGGVeritas Company, Calgary, Alberta, brian.russell@cggveritas.com

### Bertrand Six, Olivier Colnard, Jean-Philippe Coulon and Yasmine Aziez CGGVeritas Frédéric Cailly, Total

4-D Seismic Inversion: A Case Study Offshore Congo Bertrand Six, Olivier Colnard, Jean-Philippe Coulon and Yasmine Aziez CGGVeritas Frédéric Cailly, Total Summary The first 4D seismic survey in Congo was

### The GIG consortium Geophysical Inversion to Geology Per Røe, Ragnar Hauge, Petter Abrahamsen FORCE, Stavanger

www.nr.no The GIG consortium Geophysical Inversion to Geology Per Røe, Ragnar Hauge, Petter Abrahamsen FORCE, Stavanger 17. November 2016 Consortium goals Better estimation of reservoir parameters from

### Keywords. PMR, Reservoir Characterization, EEI, LR

Enhancing the Reservoir Characterization Experience through Post Migration Reprocessed (PMR) Data A case study Indrajit Das*, Ashish Kumar Singh, Shakuntala Mangal, Reliance Industries Limited, Mumbai

### The role of seismic modeling in Reservoir characterization: A case study from Crestal part of South Mumbai High field

P-305 The role of seismic modeling in Reservoir characterization: A case study from Crestal part of South Mumbai High field Summary V B Singh*, Mahendra Pratap, ONGC The objective of the modeling was to

### Robust one-step (deconvolution + integration) seismic inversion in the frequency domain Ivan Priezzhev* and Aaron Scollard, Schlumberger

Robust one-step (deconvolution + integration) seismic inversion in the frequency domain Ivan Priezzhev and Aaron Scollard, Schlumberger Summary Seismic inversion requires two main operations relative to

### Reducing Uncertainty through Multi-Measurement Integration: from Regional to Reservoir scale

Reducing Uncertainty through Multi-Measurement Integration: from Regional to Reservoir scale Efthimios Tartaras Data Processing & Modeling Manager, Integrated Electromagnetics CoE, Schlumberger Geosolutions

### Subsurface Consultancy Services

Subsurface Consultancy Services Porosity from Reservoir Modeling Perspective Arnout Everts with contributions by Peter Friedinger and Laurent Alessio FESM June 2011 LEAP Energy Main Office: G-Tower, level

### = (G T G) 1 G T d. m L2

The importance of the Vp/Vs ratio in determining the error propagation and the resolution in linear AVA inversion M. Aleardi, A. Mazzotti Earth Sciences Department, University of Pisa, Italy Introduction.

### Figure 1. P wave speed, Vp, S wave speed, Vs, and density, ρ, for the different layers of Ostrander s gas sand model shown in SI units.

Ambiguity in Resolving the Elastic Parameters of Gas Sands from Wide-Angle AVO Andrew J. Calvert - Simon Fraser University and David F. Aldridge - Sandia National Laboratories Summary We investigate the

### Elements of 3D Seismology Second Edition

Elements of 3D Seismology Second Edition Copyright c 1993-2003 All rights reserved Christopher L. Liner Department of Geosciences University of Tulsa August 14, 2003 For David and Samantha And to the memory

### Interpretation and Reservoir Properties Estimation Using Dual-Sensor Streamer Seismic Without the Use of Well

Interpretation and Reservoir Properties Estimation Using Dual-Sensor Streamer Seismic Without the Use of Well C. Reiser (Petroleum Geo-Services), T. Bird* (Petroleum Geo-Services) & M. Whaley (Petroleum

### Acoustic impedance inversion and CO 2 flood detection at the Alder Flats ECBM project

ECBM CO 2 flood detection Acoustic impedance inversion and CO 2 flood detection at the Alder Flats ECBM project Jason M. McCrank and Don C. Lawton ABSTRACT The 3D post-stack vertical component data from

### IJMGE Int. J. Min. & Geo-Eng. Vol.49, No.1, June 2015, pp

IJMGE Int. J. Min. & Geo-Eng. Vol.49, No.1, June 2015, pp.131-142 Joint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis Moslem Moradi 1, Omid Asghari 1,

### C002 Petrophysical Seismic Inversion over an Offshore Carbonate Field

C002 Petrophysical Seismic Inversion over an Offshore Carbonate Field T. Coleou* (CGGVeritas), F. Allo (CGGVeritas), O. Colnard (CGGVeritas), I. Machecler (CGGVeritas), L. Dillon (Petrobras), G. Schwedersky

### OTC OTC PP. Abstract

OTC OTC-19977-PP Using Modern Geophysical Technology to Explore for Bypassed Opportunities in the Gulf of Mexico R.A. Young/eSeis; W.G. Holt, G. Klefstad/ Fairways Offshore Exploration Copyright 2009,

### Earth models for early exploration stages

ANNUAL MEETING MASTER OF PETROLEUM ENGINEERING Earth models for early exploration stages Ângela Pereira PhD student angela.pereira@tecnico.ulisboa.pt 3/May/2016 Instituto Superior Técnico 1 Outline Motivation

### AVO Crossplotting II: Examining Vp/Vs Behavior

AVO Crossplotting II: Examining Vp/Vs Behavior Heath Pelletier* Talisman Energy, Calgary, AB hpelletier@talisman-energy.com Introduction The development of AVO crossplot analysis has been the subject of

### RESERVOIR SEISMIC CHARACTERISATION OF THIN SANDS IN WEST SYBERIA

www.senergyltd.com RESERVOIR SEISMIC CHARACTERISATION OF THIN SANDS IN WEST SYBERIA Erick Alvarez, Jaume Hernandez, Bolkhotivin E.A., Belov A.V., Hakima Ben Meradi,Jonathan Hall, Olivier Siccardi, Phil

### Sadewa Field is in Kutei Basin in the Makassar Strait between

SPECIAL Asia SECTION: Pacific A s i a P acific Distinguishing gas sand from shale/brine sand using elastic impedance data and the determination of the lateral extent of channel reservoirs using amplitude

### Estimating the hydrocarbon volume from elastic and resistivity data: A concept

INTERPRETER S CORNER Coordinated by Rebecca B. Latimer Estimating the hydrocarbon volume from elastic and resistivity data: A concept CARMEN T. GOMEZ, JACK DVORKIN, and GARY MAVKO, Stanford University,

### Estimation of Elastic Parameters Using Two-Term Fatti Elastic Impedance Inversion

Journal of Earth Science, Vol. 6, No. 4, p. 556 566, August 15 ISSN 1674-487X Printed in China DOI:.7/s158-15-564-5 Estimation of Elastic Parameters Using Two-Term Fatti Elastic Impedance Inversion Jin

### P235 Modelling Anisotropy for Improved Velocities, Synthetics and Well Ties

P235 Modelling Anisotropy for Improved Velocities, Synthetics and Well Ties P.W. Wild* (Ikon Science Ltd), M. Kemper (Ikon Science Ltd), L. Lu (Ikon Science Ltd) & C.D. MacBeth (Heriot Watt University)

### Fred Mayer 1; Graham Cain 1; Carmen Dumitrescu 2; (1) Devon Canada; (2) Terra-IQ Ltd. Summary

2401377 Statistically Improved Resistivity and Density Estimation From Multicomponent Seismic Data: Case Study from the Lower Cretaceous McMurray Formation, Athabasca Oil Sands Fred Mayer 1; Graham Cain

### Simultaneous Inversion of Pre-Stack Seismic Data

6 th International Conference & Exposition on Petroleum Geophysics Kolkata 006 Summary Simultaneous Inversion of Pre-Stack Seismic Data Brian H. Russell, Daniel P. Hampson, Brad Bankhead Hampson-Russell

### Probabilistic seismic inversion using pseudo-wells

Seismic Rock Physics Seminar Probabilistic seismic inversion using pseudo-wells Patrick Connolly*, PCA Ltd Patrick Connolly Associates Ltd. geophysics for integration Outline ODiSI: probabilistic inversion

### Derived Rock Attributes Analysis for Enhanced Reservoir Fluid and Lithology Discrimination

IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) e-issn: 2321 0990, p-issn: 2321 0982.Volume 5, Issue 2 Ver. I (Mar. - Apr. 2017), PP 95-105 www.iosrjournals.org Derived Rock Attributes Analysis

### Rock Physics Perturbational Modeling: Carbonate case study, an intracratonic basin Northwest/Saharan Africa

Rock Physics Perturbational Modeling: Carbonate case study, an intracratonic basin Northwest/Saharan Africa Franklin Ruiz, Carlos Cobos, Marcelo Benabentos, Beatriz Chacon, and Roberto Varade, Luis Gairifo,

### Summary. Seismic Field Example

Water-saturation estimation from seismic and rock-property trends Zhengyun Zhou*, Fred J. Hilterman, Haitao Ren, Center for Applied Geosciences and Energy, University of Houston, Mritunjay Kumar, Dept.