Acoustic anisotropy in rock formation

Introduction

For petroleum engineers to understand the environment that they work in, they need to comprehend rocks' physical and mechanical properties perfectly. Physical properties of rocks can include but are not limited to porosity, permeability, density, where the mechanical properties of rocks are elastic modulus, Poisson's ratio, rock strength, among many others. These properties can be obtained through lab experiments on rock core samples or through well logging and geophysical surveys.

Acoustic anisotropy

Rocks' mechanical properties affect a fundamental characteristic of rocks which is acoustic anisotropy. As defined in a research paper on "Untangling Acoustic Anisotropy," this is a directional variation in velocities with mainly two geological factors causing this phenomenon to occur: depositions and tectonic effects (Market. et al. 2015). Depositions, or layering, are usually referred to as intrinsic anisotropy, while tectonic effects, such as faults and fractures, are referred to as stress anisotropy (Market. et al. 2015).

Introduction

For petroleum engineers to understand the environment that they work in, they need to comprehend rocks' physical and mechanical properties perfectly. Physical properties of rocks can include but are not limited to porosity, permeability, density, where the mechanical properties of rocks are elastic modulus, Poisson's ratio, rock strength, among many others. These properties can be obtained through lab experiments on rock core samples or through well logging and geophysical surveys.

Rocks' mechanical properties affect a fundamental characteristic of rocks which is acoustic anisotropy. As defined in a research paper on "Untangling Acoustic Anisotropy," this is a directional variation in velocities with mainly two geological factors causing this phenomenon to occur: depositions and tectonic effects (Market. et al. 2015). Depositions, or layering, are usually referred to as intrinsic anisotropy, while tectonic effects, such as faults and fractures, are referred to as stress anisotropy (Market. et al. 2015).

For a long time, acoustic anisotropy has been described as 'black art' (Market & Tudge, 2017), which means there is so much mystery behind it. Even though the technology has been advancing by the day, this topic has not been getting the emphasis it needs from the industry, research, as well as the academia sectors, especially the latter. For a very long time, petroleum engineers have been assuming that the waves in the formation are propagating equally in all directions, meaning that they have an isotropic behavior (Armstrong, et al. 1995). However, it was noticed that waves travel through the rocks in different velocities as well as in different directions. Acoustic anisotropy has been largely ignored by exploration and production geophysicists as they were under the impression that the effect of the presence of acoustic anisotropy could be neglected. And this is precisely what describes the problem statement this research paper is mainly discussing. Acoustic anisotropy has variant applications in the industry such as fracture characterization, wellbore stability, production enhancement and optimization, seismic integration, and geosteering (Market, et al. 2015). The complexity behind the physics of acquiring and processing the data obtained for acoustic anisotropy is very high and challenging. Thus, it is vital to understand the theory behind it, which in return will aid petroleum engineers to apply and use the data gathered in different applications that will enhance the quality of the final outcome of well characterization and production optimization.

The research gaps can be summarized in the following points:

· Lack of focus on how to incorporate the topic of acoustic anisotropy in academia.

· Lack of research studies that comprehensively cover the topic of acoustic anisotropy.

· The technology used in anisotropy processing is not well explained in many research papers.

The data needed for anisotropy processing are called sonic data, which are obtained from well logging. As defined in Schlumberger Oilfield Glossary, well logging is the measurement versus depth or time, or both, and wireline logs are taken downhole, transmitted through a wireline to the surface, and recorded there (Schlumberger). The device used in obtaining the required sonic data is called sonic scanner, which is a device designed by Schlumberger specifically for advanced acoustic data acquisition.

There are three types of waves that are extremely important for this process: compressional waves, also called p-wave, shear wave, and stonely waves (Market, et al. 2015). The first is influenced by stress or intrinsic anisotropy, while a shear wave will show as being perpendicular to the wellbore and polarizes in the presence of stress or intrinsic anisotropy, and it is mainly sensitive to geometric Anisotropy (Market, et al. 2015). And finally, stonely waves are sensitive to velocity variations perpendicular to the wellbore. It travels along with the interface between the borehole fluid, and the formation and particle motion is parallel to the axis of the wellbore (Market, et al. 2015).

In terms of types of anisotropy, this research paper will mainly focus on stress-induced anisotropy and stress caused by fractures in the formation. To distinguish between the two types, flexural dispersion curves will be required to check whether the fast and slow shear curves are separated and at the same time they are parallel to each other, this implies that it is caused by fractures, on the other hand, if the curves are intersecting each other, meaning that the anisotropy, in this case, is caused by stress.

Understanding acoustic anisotropy in rock formation and its science is crucial for a wide range of applications. Still, most importantly, it will make a huge difference and will lead to significant improvements and enhancements in the way petroleum engineers characterize, evaluate, and develop oil and gas reservoirs. In addition to increasing the productivity of the well through knowing the directions of the present fractures, leading to precisely knowing the ways a well should be drilled to have the optimum possible production. The impact and industrial applications of this research paper can be summarized in the following bullet points:

· Understanding acoustic anisotropy will help petroleum engineers have a better understanding of the environment they work in, allowing them to have better reservoir characterization.

· Fracture characterization is followed by increasing productivity.

· Wellbore stability.

Moreover, it is essential to note that formation stresses have an important impact on oil and gas reservoir development and operations. Accurate information about the stress in the formation aids petroleum engineers to conduct proper planning for the well path, improve ompletion strategies, and maintain borehole stability (Zheng, 2009)

The contributions that will be made by this research paper mainly focus on providing an overview of the topic of acoustic anisotropy, its applications in the industry, how to determine whether or not the reservoir of interest has intervals of anisotropy, and if so, what caused it and how to handle it efficiently. These contributions are primarily significant for petroleum engineers who currently work in the field, as well as for petroleum engineering undergraduates, as it broadens their perspective on acoustic logs and their relation to anisotropy in the formation. The following bullet points summarize the contributions this research paper aims to provide:

· A thorough and complete overview of the topic of acoustic anisotropy to be available for petroleum engineers and petroleum engineering undergraduates.

· Detailed methodology on how to confirm the presence of anisotropy and determine its cause.

Similar to what has been mentioned in the previous paragraph, the short-term objective of this research is to simply introduce acoustic anisotropy, show how we can identify anisotropy intervals, and identify if they are caused by stress or fractures. And regarding the long-term objectives, this research is expected to aid petroleum engineers in applying the science behind anisotropy in different applications, such as fracture characterization, production optimization, wellbore stability, and hydraulic fracture monitoring. When this is achieved, especially the points related to production optimization, it is expected that the oil and gas industry will be able to meet the global energy demand and make more profit.

Determining intervals with acoustic anisotropy

In order to perform anisotropy processing and determine the intervals where anisotropy is present, the first step that needs to be done is perform well logging. Along other tools from which density, porosity, and other important parameters are obtained, the logging tool that shows the sonic waves in the formation is called sonic scanner. After getting these data, they are transferred to petrophysicists who are well knowledged and experienced in this field in where they conduct anisotropy processing, and the particular steps to do that are as follows:

1- Gather necessary information from well logging. Two sets of data for the same interval will be generated, while each set contains Gamma Ray log, density, caliper, etc. In addition, a tool called sonic scanner, is run to get another two sets of data containing the paramteres necessairy for acoustic anisotropy processing such as the waveforms.

2- Plot gamma ray coming from both sources, as well as porosity and neutron density logs.

3- The peaks will show on different points, even though the well logging tool is detecting the ame formation and the same interval. Hence, a process of depth matching the logs will be conducted and then the edited version will be saved. After that, the depth shift tbale should be applied to all other logs present in the dataset.

4- Prepare and filter the data in the data preparation tab in the Acoustic Interpretation Suite.

5- Quality Check (QC) the data by initializing a dispersion plot containing four waveforms, namely: far-dipole, x-dipole, y-dipole, and stonely. The point where a dispersion plot should be initialized is at porosity equal to 0%

6- The model will most probably not match the data points, hence, a change in the default parameters so that data points can match the model is necessary.

7- Conduct two parts of data processing as follows:

a. Delta-T processing:

Choose sonic scanner option from the drop down menu.
Workflow will show up, conduct each in the same displayed order.
Final compressional slowness will be displayed, calculate VpVs (ratio of P wave to S wave) and Poisson’s ratio.
Do depth shifting for compressional and shear waves.
Plot VpVs and compressional slowness on a cross plot to determine the formation type and to determine intervals containing gas.

b. Anisotropy processing:

Choose anisotropy processing from AIS.
Follow the workflow and conduct anisotropy processing.
New set of data will be obtained and a new log view will be initialized.

8- From the generated log view, anisotropy is present where cross energy, slowness, time, are more than 0% as well as having an error equal to zero in the third track.

9- Oppositely, isotropy is present is when the cross energy, slowness, time, are equal to 0% and the error in the third track is more than zero.

Conclusion

This project aimed to introduce the topic of acoustic anisotropy to both the industry and academia sector for the benefits it can impose when properly understood. And through this project, this objective was achieved by first of all introducing the theory behind the topic, introduce different types of anisotropy that could be present in the formation, explain what kinds of waves are required to confirm the presence of anisotropy, and how to utilize Techlog software for that matter, and finally, to know how can petroleum engineers make use of the data obtained in order for them to make better decisions in terms of the recovery technique used which in return will optimize the production.

The data set provided was imported to techlog and three intervals of anisotropy were present, where two of them were caused by the presence of fracture, and the third one appeared as a result of stress induced. It is essential for petroleum engineers to gather this information because knowing the interval where a natural fracture is present can aid them to properly plan on how to complete the well and produce from it. Moreover, knowing the interval where stress is present, and knowing its direction, help petroleum engineers to know at what directions can they implement hydraulic fracturing in order to maximize contact with the reservoir and hence maximize oil and gas production

References

Armstrong, P., Ireson, D., Chmela, B., et al. 1995. Oilfield Anisotropy: The Promise of Elastic Anisotropy. Schlumnerger Oilfield Review, 36-47. https://www.slb.com/-/media/files/oilfield-review/p36-48

Market, J., Mejia, C., Mutlu, O. et al. 2015. Untangling acoustic anisotropy. Society of Petrophysicisits and Well Log Analysts (SPLWA). Presented at the SPLWA 56^th Annual Logging Symposium, Oklahoma, USA, June. SPWLA-2015-v56n5a1

Market, J. and Tudge, J. 2017. A Layman's Guide to Acoustic Anisotropy. Society of Petrophysicisits and Well Log Analysts (SPLWA). Presented at the SPLWA 58^th Annual Logging Symposium, Long Beach, California, USA, 18-22 July. SPWLA-2017-Z

Schlumberger. Well log. Schlumberger Oilfield Glossary.

https://glossary.oilfield.slb.com/en/Terms/w/well_log.aspx (Accessed 25 Sep 2021).

Zheng, Y., Tang, X. et al. 2009. Identifying Stress-Induced Anisotropy And Stress Direction Using Cross-Dipole Acoustic Logging. Society of Petrophysicists and Well Log Analysts (SPLWA). Presented at the SPWLA 50^th Annual Logging Symposium, The Woodlands, Texas, United States, 21-24 June. SPLWA-2009-21660

Acoustic anisotropy in rock formation

Contents

Introduction