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«UNIVERSITY OF OKLAHOMA GRADUATE COLLEGE QUANTITATIVE GEOPHYSICAL INVESTIGATIONS AT THE DIAMOND M FIELD, SCURRY COUNTY, TEXAS. A DISSERTATION ...»

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UNIVERSITY OF OKLAHOMA

GRADUATE COLLEGE

QUANTITATIVE GEOPHYSICAL INVESTIGATIONS AT THE DIAMOND M

FIELD, SCURRY COUNTY, TEXAS.

A DISSERTATION

SUBMITTED TO THE GRADUATE FACULTY

in partial fulfillment of the requirements for the Degree of

DOCTOR OF PHILOSOPHY

By

OSWALDO ERNESTO DAVOGUSTTO CATALDO

Norman, Oklahoma

QUANTITATIVE GEOPHYSICAL INVESTIGATIONS AT THE DIAMOND M

FIELD, SCURRY COUNTY, TEXAS.

A DISSERTATION APPROVED FOR THE

CONOCOPHILLIPS SCHOOL OF GEOLOGY AND GEOPHYSICS

BY ______________________________

Dr. Kurt J. Marfurt, Chair ______________________________

Dr. Carl Sondergeld ______________________________

Dr. John Pigott ______________________________

Dr. G. Randy Keller ______________________________

Dr. Steve Roche ______________________________

Mr. J. W. Thomas © Copyright by OSWALDO ERNESTO DAVOGUSTTO CATALDO 2013 All Rights Reserved.

Ad maiorem Dei gloriam To Alessandro and Andrea Acknowledgements First of all I thank God for all. My life has been a rocky road mixed with flat paths. I know it is all has been God’s plan for me.

This work has been influenced by several individuals in many ways. When I write this work it is not only restricted to the results contained in this thesis but all the learning in all the different aspects of my life that have been somewhat touched or modeled those individuals. Unfortunately it is impossible for me to list all that learning but what I can do is dedicate a few words in this section to each one of those individuals. Just a few because if not this would be an infinite chapter.

I will begin with my parents Maria Teresa Cataldo and Oswaldo Davogustto.

Now that I am a father myself I understand just a little everything that you did and what that sacrifice meant for me. Not in vain there is a saying that you will learn to be a son once you become a parent. Well I thank you both, I owe you all that I have and all that I am. I thank Andrea Miceli, my wife and companion. With you I have become that which I would not have dreamed of being. It is because of you I push myself more and more to become a better man and a better husband. I thank Giovanni Davogustto, my brother.

I thank Dr. Roger A. Young; my life at OU started because you believed in me when I did not even had an idea of what I wanted to be or what I wanted to do. I miss you a lot. I thank Dr. Kurt J. Marfurt, I always felt that life made me your student by chance and I could not have a better example of good luck for me. With your guidance I have learned seismic interpretation, processing, scientific writing, common sense. If I know geophysics it is because of you. I thank Dr. Carl Sondergeld, you have taught me

–  –  –

their behavior at any scale. More important I have learned from you to be aware and look for the limitations and assumptions on any technique thus improving my understanding and providing better interpretations. I thank Dr. John Pigott, you started the curiosity on my about the carbonates. I have become passionate about their complexity and what they represent for both, the academy and the industry. I thank Dr.

G. Randy Keller; your help through these years at OU has been invaluable to me. I admire your dedication to your students and your ability to cheerfully give advice. I thank Dr. Steve Roche; we share that passion for shear-wave data that only a few understand. I have had much fun working with you doing the detective work to understand the shear-wave phenomena and putting all the pieces of this puzzle together.

I thank J. W. Thomas; you have taught me about processing and have been a friend to me. I thank Dr. J. Tim Kwiatkowski; we have had fun times together. I have learned from you the importance of all that math and physics that seemed not important when I was an undergrad. I thank Mike Burnett; you have always encouraged me to become a better geophysicist and have taught me the practical aspects of the business.

I would also like to thank Alison Small, Dr. Roger Slatt, Dr. Lynn Soreghan, Teresa Hackney, Nancy Leonard, Donna Mullins, Jocelyn Cooke, Adrianne Fox, Jody Foote and Alison Richardson.

I would like to thank my brothers in arms on this journey Bradley Wallet, Richard Brito, Alfredo Fernandez and Benjamin Dowdell. It has been fun times and there are more to come. There is a long list of people that I would like to thank that I have not mentioned. This is a thank you for y’all.

–  –  –

Acknowledgements

Table of Contents

List of Tables

List of Figures

1. Abstract

2. Introduction

3. Motivation and Objectives

References

4. Poreshape estimation for the Horseshoe Atoll carbonate reservoir, Midland Basin, Texas: An integrated approach

Abstract

Introduction

Geolgical Background

Methodology

Laboratory measurements

Well logs evaluation





Results and Discussion

Porosity and Permeability

Compressional and Shear velocities

Biot-Gassmann modeling

Pore type characterization using Kuster and Toksöz scattering model on core samples

–  –  –

logs

Conclusions

Acknowledgements

List of Figures

References

5. Improving the bandwidth of shear impedance and density estimates using nonstretch nmo

Abstract

Introduction

Matching pursuit non-stretch nmo (MPNMO)

Application

Wavelet response and Seismic well-ties

Simultaneous pre-stack inversion

Conclusions

Acknowledgements

List of figures

References

6. 3D Alford rotation analysis for the Diamond M field, Midland Basin, Texas... 81 Abstract

Introduction

Automatic Alford rotation using least squeares minimization

–  –  –

dataset

Field, Radial-Transverse, and Alford rotated data comparison

Alford fracture azimuth map

Processing considerations after pre-stack automatic Alford rotation................. 88 Conclusions

Acknowledgements

List of Figures

References

7. Quantitative geophysical reservoir characterization at the Diamond M field, Texas

Abstract

Introduction

Geolgical Background

Data Description

Time structure maps and estimated anisotropy

Geometric attribute reservoir description

Integration of core, log data and seismic inversion data for porosity prediction... 123 Correlation of attributes to production data

Conclusions

Acknowledgements

List of Figures

References

–  –  –

Abstract

Introduction

Methodology Review

Spectral Ridges and Pseudo-deconvolution

Spectral Discontinuities and Phase Residues

Application of CWT Attributes to improve reservoir geometry interpretation...... 184 Carbonate environment example (Midland Basin, TX)

Clastic environment example (Anadarko Basin, OK)

Conclusions

Acknowledgements

List of figures

References

9. Conclusions

10. Recommendations

Appendix A: Diamond M prestack compressional data processing

Appendix B: Programs Rotate 2C by 2C and Alford azimuth map

Program rotate 2c by 2c

Computation flow chart

Running Rotate_2C_by_2C

Program Alford azimuth map

Computation flow chart

–  –  –

Table 5.1: Correlation coefficients for the well ties using conventional migration and the MPNMO corrected gathers for the full and the angle limited stack data.

We observe a higher correlation coefficient between the well synthetics and the MPNMO corrected data. Also note that the near, mid, and far angle gather well-ties show more consistency in the correlation coefficients behavior than the conventional migration data............... 60 Table 5.2: Correlation coefficients of the inversion analysis for the conventional migration and the MPNMO data.

Table 7.1: Multi-linear regression for porosity prediction from P-impedance, Simpedance, and density correlation table.

–  –  –

Figure 4.1: (a) Location of the Diamond M Field, Scurry County, TX.

(b) Time structure map indicating the location of wells used in this study. The largest carbonate buildup is defined by the red and yellow colors in (b)

Figure 4.2: Helium porosities as a function of confining pressure for (a) well E and (b) well J.

The decrease in porosity with increasing confining pressure suggests that a fraction of the porosity has a low aspect ratio. The relative linear behavior of the porosity curves with pressure suggests that cracks do not possess a significant volume.

The average change in porosity for both datasets is about 16% or 3.4%/1000psi......... 20 Figure 4.3: Klinkenberg corrected permeabilities as a function of confining pressure for (a) well E and (b) well J. Permeability shows no strong dependency on pressure this implies that permeability is not crack dependent.. The average change in permeability for both datasets is 5%

Figure 4.4: Comparison between (a) helium pycnometer-porosimeter (HPP) porosity versus Φhe and (b) Φhe versus ΦNMR for wells E and J.

There is a good agreement between all measurements. This is an important result because implies that we will have a very good estimate of true porosity from NMR borehole tools.

Figure 4.5: Klinkenberg permeability versus NMR for wells E and J.

There is a positive correlation between methods but the difference between the measured and predicted permeabilities is on average about one order of magnitude.

Figure 4.6: (a) Compressional and (b) shear velocities versus confining pressure for well E.

Both datasets show a nonlinear increase with the increase of confining pressure.

At low pressures we observe a rapid increase of velocities due to reduction of crack

–  –  –

aspect ratio porosity. The average change in compressional and shear velocities with pressure for this well is 5% in both cases.

Figure 4.7: (a) Compressional and (b) shear velocities versus confining pressure for well J.

Both datasets show a nonlinear increase with the increase of confining pressure.

At low pressures we observe a rapid increase of velocities due to reduction of crack porosity. The changes more gradual observed at high pressures are possibly due to high aspect ratio porosity. The average change in compressional and shear velocities with pressure for this well is 5% in both cases.

Figure 4.8: Dry versus wet shear modulus computed from the shear velocities and densities for wells E and J.

Values align on a 1:1 trend line as inferred from BiotGassmann equations and indicating no fluid induced framework changes.

Figure 4.9: Measured (Kmeas) versus predicted bulk modulus computed from compressional and shear velocities for wells E and J.

We observe a good correlation in general between the measured and the predicted bulk saturated modulus. This also confirms that Biot-Gassmann theory works for this reservoir. We observe a change in behavior for samples with a Kmeas greater than 42 GPa that correspond to a porosities lower than 8%. This result is in agreement with the findings by Bhagat et al. (2012).

Bhagat et al. (2012) results are plotted in green for reference.

Figure 4.10: Normalized dry bulk modulus versus porosity for (a) well E and (b) well J.

Black lines indicate the theoretical solution for the effect of crack aspect ratio on the bulk modulus. Note that for both wells porosity has an aspect ratio lower than 1 indicating crack like porosity.

–  –  –

J. Black lines indicate the theoretical solution for the effect of crack aspect ratio on the bulk modulus. Note that for both wells most porosity has an aspect ratio lower than 1 indicating crack like porosity.

Figure 4.12: (a) Normalized dry bulk modulus versus porosity for samples E23, E34 and E62 of well E.

(b), (c) and (d) are the respective thin section photographs for the corresponding samples. There is a good agreement between the predicted aspect ratio for the samples and the observed aspect ratio in the thin section photographs. (a) Black lines indicate the theoretical solution for the effect of crack aspect ratio on the bulk modulus.

Figure 4.13: Type log from the Horseshoe atoll reservoir interval.

Suite of logs displayed is from well J. Continuous curves indicate original or derived logs. Dots indicate measured property values from core. Overall we have a good agreement between log and sample data. We attribute some of the scatter to borehole effects observed in the differential caliper (DCAL) and in the density correction (HDRA) logs.

Figure 4.14: Saturated core versus log (a) bulk density and (b) total porosity measurements.

Both cross-plots indicate a good agreement between core and log measurements. We attribute the scatter to borehole conditions.

Figure 4.15: Saturated core versus log (a) compressional and (b) shear velocity measurements.

Both cross-plots indicate a good agreement between core and log measurements and of statistical significance. We attribute the scatter to borehole conditions.

–  –  –

M08 and M05. Most of the pore aspect ratio is distributed between 0.1 and 0.01. These results agree with observations shown in Figure 11

Figure 4.17: (a) Normalized bulk modulus vs.



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