Methods for Processing Multi-Temporal Composite Synthetic Aperture Radar Data to Detect Land Surface Displacement / Методы обработки мультивременных композитных радиолокационных данных для регистрации движения земной коры тема диссертации и автореферата по ВАК РФ 00.00.00, кандидат наук Хатамиафкуиех Джавад

• Хатамиафкуиех Джавад
• кандидат наук
• 2024

Оглавление диссертации кандидат наук Хатамиафкуиех Джавад

TABLE OF CONTENTS

ACKNOWLEDGMENTS

ABSTRACT

INTRODUCTION

CHAPTER 1. LITERATURE REVIEW

1.1. Overview of Remote sensing and InSAR

1.1.1. Synthetic Aperture Radar

1.1.2. Antennas And Short Pulses Of Radio Frequency Energy

1.1.3. Resolution of Radar Image

1.1.4. Interferometric Synthetic Aperture Radar (InSAR)

1.1.5. Interferometric Coherence

1.2. Overview of SBAS-InSAR for land displacement monitoring

1.2.1. Time Series InSAR

1.2.2. Small Baseline Subset (SBAS) InSAR

1.2.2.1. Principle

1.3. Previous research on InSAR

1.4. Limitations and challenges of SBAS-InSAR

CHAPTER 2. METHODOLOGY

2.1. Study Area: Oil and Gas Fields in Kern County, California

2.1.1. ntroduction The San Joaquin Valley (SJV)

2.1.2. Introduction to Kern County, California

2.1.3. Overview of the North Belridge Oil Field

2.1.4. Overview of the South Belridge Oil Field

2.1.5. Overview of the Midway-Sunset Oil Field

2.1.6. Overview of the Lost Hills Oil Field

2.1.7. Overview of The Elk Hills Oil Field

2.1.8. Geological Setting

2.1.9. Geochemical Characteristics

2.1.10. Geophysical Properties

2.1.11. Hydrology

2.2. Data Sources

2.2.1. Sentinel-1 data acquisition

2.2.2. Comet Portal processing

2.2.3. Ground-based Measurements

2.2.3.1. Field data

2.2.3.1.1. Mechanism for Upward Fluid Flow

2.2.3.2. GPS DATA

2.3. SBAS_InSAR

2.4. LiCSAR

2.4.1. LiCSAR System Architecture

2.4.2. LiCSAR Processing Chain

2.5. Licsbas toolbox processing

2.6. Decomposition of ascending and descending data

CHAPTER 3. RESULTS

3.1. Introduction

3.2. Data Pre-processing

3.2.1. LiCSAR File Structure and Products Details

3.2.2. Baseline connection network plot

3.3. Digital Elevation Models

3.4. Interferogram generation in LiCSAR

3.5. Phase Unwrapping

3.6. Time Series Analysis

3.6.1. Masking

3.6.2. Average value of the interferometric coherence across the stack

3.6.3. Standard deviation of the velocity

3.6.4. Number Of Unwrapped Interferograms

3.6.5. Maximum Time Length Of The Connected Network

3.6.6. Number Of Gaps In The Interferogram Network

3.6.7. Spatiotemporal Consistency

3.6.8. Number Of Interferograms With No Loops

3.6.9. Number Of Unclosed Loops

3.6.10. Small Baseline (Sb) Inversion

3.7. Visualization of the Results

3.8. Spatiotemporal filtering

3.9. Mask Time Series

3.10. Decomposition Of Ascending And Descending Data

3.11. Validation and Interpretation

3.11.1. Uncertainty

3.12. Integration of the Results

3.12.1. Displacement Trend In Northern Belridge Oil and Gas Field

3.12.2. Displacement Trend In South Belridge Oil and Gas Field

3.12.3. Displacement Trend In Elk Hills Oil and Gas Field

3.12.4. Displacement Trend In Lost Hills Oil and Gas Field

3.12.5. Displacement Trend In Midway-Sunset Oil and Gas Field

3.13. Interpretation of Results

CONCLUSION

LIST OF ABBREVIATIONS

REFERENCES

APPENDIX I. List Of Images For The Ascending Orbit Frame ID 137a_05534_131822

APPENDIX II. List Of Images For The Descending Orbit Frame ID 144d_05501_131413

APPENDIX III. List Of Output Data From Licsar For The Ascending Orbit Frame ID

137A_05534_131822

APPENDIX IV. List Of Output Data From Licsar For The Descending Orbit Frame Id

144d

Введение диссертации (часть автореферата) на тему «Methods for Processing Multi-Temporal Composite Synthetic Aperture Radar Data to Detect Land Surface Displacement / Методы обработки мультивременных композитных радиолокационных данных для регистрации движения земной коры»

ABSTRACT

An important environmental issue brought on by oil and gas extraction operations is land displacement. Interferometric Synthetic Aperture Radar (InSAR) has developed into a useful instrument for tracking land displacement at a high spatial resolution in recent years. InSAR is used in this research to examine the patterns of land displacement linked to four oil fields in Kern County, California.The five oil and gas fields in Kern County that are the subject of this research are North Belridge, South Belridge, Midway-Sunset, Lost Hills, and Elk Hills.

Time-series analysis was performed to examine the temporal evolution of land displacement. In this zone, we use the Sbas-insar approach to figure out land displacement.The LicSAR( Comet Portal )and Liscbas toolbox were used to analyze Sentinel-1 satellite data collected between 2014 and 2022. In an ascending orbit (LiCSAR frame ID 137A_05534_131822). The observation period for this frame was from 31 January 2015 to 15 August 2021, which is approximately 6.6 years. The associated network consisted of 256 images and 1499 interferograms [74]. On the other hand, in a descending orbit (LiCSAR frame ID 144D_05501_131413). The observation period for this frame was from 08 November 2014 to 07 November 2021, which is approximately 7 years. The associated network consisted of 266 images and 954 interferograms. The data were decomposed into ascending and descending data to identify vertical and (Eest-West) horizontal Displacment.

We used 85 GPS stations in central California for the accuracy evaluation. as GPS measurements and SBAS InSAR data different The east-west direction has an RMSE of 1.89 and an R-squared value of 0.9, while the vertical direction has an RMSE of 2.4 and an R-squared value of 0.94.

The results revealed that all five oil fields had evidence of land subsidence, with the South Belridge Oil Field experiencing the greatest rates of subsidence. Land displacement rates were found to vary considerably over time and to be affected by a number of elements, such as oil extraction activities and natural occurrences like drought.

Oil and gas production, groundwater pumping, and natural compaction of sedimentary layers were found to be the reasons of the land subsidence. The research emphasizes the significance of keeping an eye on land displacement in oil fields to guarantee the security of local residents and infrastructure. The study advances the discipline by demonstrating InSAR's usefulness for tracking land displacement in oil fields.The study also covered the drawbacks and possible paths for future research in using InSAR to track land displacement brought on by oil and gas extraction activities.

The study's limitations are addressed, including those related to the InSAR method, the data, and the requirement for additional research to fully comprehend the causes of land displacement.

Keywords: Land displacement, Interferometric Synthetic Aperture Radar (InSAR), Sentinel-1, oil and gas industry, Kern County, California.

INTRODUCTION

Relevance of Research

Despite the increasing use of SAR to monitor land moements, there are still many challenges that need to be addressed. One of the biggest challenges is the complexity of SAR data processing, which requires specialized knowledge and expertise [1]. Moreover, systematic and comprehensive analysis of SAR data is required to yield valuable information that can be used to understand the causes and effects of land displacement. Oil and gas exploration and production includes oil and gas drilling, production, transportation and storage [2]. These activities can result in land subsidence, uplift, and other forms of land displacement, leading to various ecological and socioeconomic problems. Although several studies have examined the impact of oil and gas activity on land transfer, comprehensive studies examining the patterns and causes of land transfer in different oil and gas fields are lacking [3]. Furthermore, the accuracy of SAR data for detecting and monitoring land movements can be affected by various factors such as the spatial and temporal resolution of the data, the type of SAR sensor used, atmospheric effects, and surface properties [4, 5]. Therefore, it is important to investigate the factors that affect the accuracy of SAR data for land displacement monitoring and to develop robust data processing and analysis methods to enhance result accuracy [6].

This study aims to explore the application of Synthetic Aperture Radar (SAR) data in monitoring land displacement within oil and gas fields and to develop optimized methods for data processing and analysis to enhance the accuracy and reliability of displacement measurements [1]. The study aims to address the challenges associated with SAR data processing and analysis and to identify the patterns and potential causes of land displacement in different oil and gas fields. This research will also contribute to improving the accuracy of SAR data for land displacement monitoring and provide valuable information for understanding the ecological and socioeconomic implications of land displacement in oil and gas fields.

The San Joaquin Valley (SJV) in California, USA, is a region of great agricultural importance and The study area is a major oil and gas production hub, but it faces challenges due to land subsidence, which poses significant economic and environmental risks [7]. Factors such as groundwater depletion, oil and gas extraction contribute to this subsidence, intensifying the need for reliable monitoring to mitigate these impacts and the construction of large infrastructure projects, such as canals, are some of the factors that can contribute to land subsidence in the SJV [8].

The San Joaquin Valley in California is known for its oil and gas fields, which have been subjected to extensive extraction activities over the years. However, these activities have been shown to cause ground displacement and subsidence in the region, leading to potential environmental and economic impacts [3,8,9]. Traditional ground-based monitoring techniques face significant limitations in both

coverage and accuracy, rendering them inadequate for effectively detecting and tracking land movement over large areas. These methods often lack the spatial reach and precision needed to capture subtle changes across extensive regions, highlighting the need for more advanced monitoring approaches to achieve comprehensive and reliable displacement detection. [1].

To address these limitations, Synthetic Aperture Radar Interferometry (InSAR) has emerged as a powerful tool for monitoring ground displacement over large areas with high accuracy and resolution [10]. In particular, the Small Baseline Subset (SBAS) technique has been widely used for monitoring subsidence and displacement in oil and gas fields [6]. Despite its advantages, the application of InSAR and SBAS in oil and gas fields still faces challenges such as atmospheric disturbances and phase unwrapping errors [7].

Therefore, the problem statement of this study is to investigate the application of SBAS InSAR for monitoring displacement and subsidence in oil and gas fields in the San Joaquin Valley, with the aim of identifying the factors that affect the accuracy and reliability of the technique in this region. This study will address the limitations and challenges of traditional monitoring techniques and provide insights into the potential of InSAR as a cost-effective and efficient tool for monitoring ground displacement in oil and gas fields.

In particular, the Small Baseline Subset (SBAS) approach, a widely used InSAR technique, has been employed in recent years for monitoring land displacement in various parts of the world, including oil and gas fields. This approach uses a stack of SAR images to calculate phase differences between them and to estimate the displacement rate over time.

While SBAS-InSAR has shown great potential for monitoring land displacement in the SJV, there is a lack of comprehensive studies that examine the patterns and causes of land transfer in different oil and gas fields. Moreover, the interpretation and integration of the large amount of SAR data generated by this approach can be challenging, requiring specialized knowledge and expertise. Therefore, the present study aims to address these challenges by utilizing the SBAS-InSAR approach to monitor land displacement in oil and gas fields in the SJV. By doing so, This study aims to deepen the understanding of the causes and effects of land subsidence in the region, providing valuable insights that can support informed decision-making for sustainable land management. By identifying patterns and underlying factors of displacement, this research can guide strategies to mitigate subsidence impacts, promoting more effective and resilient land use practices in affected areas.

Degree of Development of the Research Topic

Oil and gas production is a major industry that contributes significantly to the global economy. However, the extraction of resources like oil, gas, and groundwater can lead to land subsidence, which threatens both environmental stability and human safety. Land subsidence refers to the gradual sinking or settling of the Earth's surface, often triggered by factors such as groundwater depletion or the

extraction of natural resources. This phenomenon can result from natural processes, but it is also frequently exacerbated by human activities, including intensive oil and gas production [3].

Subsidence can cause a range of problems, including damage to infrastructure like buildings and roads, decreased agricultural productivity, and increased risk of flooding. Additionally, subsidence can lead to the release of greenhouse gases like methane, which can contribute to climate change [11]. As such, it is important to monitor land subsidence in areas where oil and gas production is taking place [12].

There are several methods available for monitoring land displacement in oil and gas fields, including ground-based techniques like leveling and GPS, as well as satellite-based techniques like interferometric synthetic aperture radar (InSAR) [13, 75]. Of these, InSAR is particularly attractive due to its high spatial and temporal resolution. This technique can detect subsidence on the order of millimeters per year, which can be crucial for detecting and mitigating land movement in its early stages. Additionally, InSAR can be applied over large areas, allowing for comprehensive monitoring of entire oil and gas fields [4,14].

Background and Motivation

One specific technique that has shown promise for oil and gas field monitoring is the Small Baseline Subset (SBAS) InSAR technique. SBAS-InSAR is a time-series analysis technique that uses a sequence of SAR images to detect and monitor ground deformation[13]. This technique is particularly useful for monitoring large areas over long periods of time, and it has been applied successfully in a variety of contexts, including mining subsidence, glacier monitoring, and urban subsidence[1].Despite its advantages, the use of SBAS-InSAR for oil and gas field monitoring is still relatively new, and there are several challenges to overcome[12]. One of the primary challenges is the need for accurate and up-to-date ground truth data to validate the satellite measurements. Additionally, the geology and topography of different oil and gas fields can vary widely, which can affect the accuracy of the measurements [14]. Finally, there is a need for continued research and development in order to refine and improve the SBAS-InSAR technique for oil and gas field monitoring.(Land displacement is a major environmental problem caused by various anthropogenic and natural factors. In recent years, Synthetic Aperture Radar (SAR) Interferometry (InSAR) has emerged as a powerful tool for monitoring land displacement. In particular, the use of the Small Baseline Subset (SBAS) approach in InSAR has enabled the detection and measurement of small changes in the Earth's surface over large areas. This technique has been widely applied in the oil and gas industry to monitor land displacement caused by exploration and production activities [13].

Also the increasing use of SAR to monitor land movements, there are still many challenges that need to be addressed. One of the biggest challenges is the complexity of SAR data processing, which requires specialized knowledge and expertise. Moreover, systematic and comprehensive analysis of SAR

data is required to yield valuable information that can be used to understand the causes and effects of land displacement [10].Land displacement is a widespread phenomenon caused by various natural and anthropogenic factors, including oil and gas activities, subsidence due to groundwater extraction, and natural geological processes [3]. In particular, Activities related to oil and gas exploration and production can lead to land subsidence, uplift, and other types of ground displacement, resulting in a range of ecological and socioeconomic challenges. To monitor and measure these land changes effectively, various techniques have been established, including GPS, leveling, and advanced remote sensing methods like Synthetic Aperture Radar Interferometry (InSAR) and Differential SAR Interferometry (DInSAR). These methods provide essential insights into the scale and nature of land displacement in affected areas [13,15].

In particular, the use of SAR and InSAR has gained significant attention in recent years due to their high spatial and temporal resolution and ability to detect even small changes in land surface elevation. One commonly used approach is the Small Baseline Subset (SBAS) InSAR technique, which uses a time series of SAR images to generate a high-resolution displacement map of the study area [9]. This technique has been widely used to monitor land displacement in various oil and gas fields around the world [16], including the San Joaquin Valley in California, the North Sea in Europe, and the Niger Delta in Africa.

Despite the increasing use of SAR and InSAR techniques for monitoring land displacement, there are still many challenges that need to be addressed [17]. One of the biggest challenges is the complexity of SAR data processing, which requires specialized knowledge and expertise. Moreover, systematic and comprehensive analysis of SAR data is required to yield valuable information that can be used to understand the causes and effects of land displacement [11,18]. Therefore, this study aims to use the SBAS InSAR approach to monitor and quantify land displacement in oil and gas fields in the San Joaquin Valley, California, and to investigate the causes and effects of su Land displacement in oil and gas fields is a growing concern worldwide, as it can lead to ecological and socioeconomic problems [7]. The San Joaquin Valley (SJV) in California is a region with a long history of oil and gas exploration and production, where land displacement has been observed [14, 19]. The use of Synthetic Aperture Radar Interferometry (InSAR) has proven to be a valuable tool for monitoring land displacement in oil and gas fields [14]. InSAR allows for the detection of even small land movements with high spatial resolution over large areas [21]. Moreover, the application of the Small Baseline Subset (SBAS) approach to InSAR data has enabled the detection of both vertical and horizontal ground movements with millimeter-level accuracy (Cheraghi et al., 2019; Huang et al., 2016). However, the processing of SAR data is complex and requires specialized knowledge and expertise [1]. Moreover, there is a significant gap in systematic and comprehensive studies that analyze the patterns and causes of land displacement across various oil and gas fields [16]. Therefore, the aim of this study is to investigate the use of the SBAS-InSAR approach

for monitoring and analyzing land displacement in oil and gas fields in the SJV, in order to gain a better understanding of the causes and effects of land displacement and contribute to the development of effective management strategies.

Research Objectives

The main objective of this research is to investigate the feasibility and effectiveness of Small Baseline Subset (SBAS) InSAR technique for monitoring land displacement in oil and gas fields. The specific objectives are:

• Develop and Apply SBAS-InSAR for Monitoring Land Displacement: Utilize the SBAS-InSAR technique through the LiCSBAS toolbox and Comet Portal to monitor land displacement, leveraging Sentinel-1 satellite data for precise, time-sensitive measurements of ground movement.

• Analyze and Interpret Displacement Patterns: Conduct an in-depth analysis of SBAS-InSAR results to identify possible hazards and underlying causes of land displacement in oil and gas field areas, correlating observed surface changes with contributing factors.

• Evaluate Methodology and Technical Constraints: Assess the limitations and challenges of the SBAS-InSAR technique in capturing land displacement within oil and gas fields, considering issues like atmospheric interference, topographic effects, and data decorrelation.

• Enhance SAR Data Accuracy for Improved Monitoring: Implement methods to enhance the accuracy of SAR data in tracking land displacement, aiming to produce high-quality, reliable displacement maps and time series analyses.

• Validate Methodology Against GPS Data for Reliability: Assess the reliability and accuracy of displacement measurements by comparing InSAR results with GPS station data, validating the methods for monitoring ground dynamics and ensuring robust data interpretation.

• Investigate Factors Affecting Land Displacement: Analyze the factors influencing surface displacement within oil and gas fields, including oil extraction, groundwater pumping, and natural subsidence, to understand their combined effects on the Earth's crust dynamics and spatial displacement patterns.

Scientific novelty of the research

This research will focus on:

• A new approach to semi-autonomous extraction of millimeter-level deformations from InSAR radar time series is proposed, aimed at providing a comprehensive understanding of the dynamic behavior of the Earth's surface within oil and gas field areas.

• A new structure for analyzing temporal changes in displacement patterns with high spatial resolution is introduced. The integration of detailed accuracy assessment methods, including comparison with GPS station data, enhances the reliability and justification of the developed methods.

• A method for Solving the ill-posed equation by CSBAS method addresses the ill-posed nature

of the equation by introducing the minimum norm benchmark equation, which acts as a foundational constraint to stabilize the solution process.

• A method for measuring multidimensional deformation using time series of SAR images from both ascending and descending satellite orbits is proposed.

• A methodology for monitoring land surface displacement in areas with low coherence and varying degrees of spatiotemporal decorrelation is developed by tracking pixel displacement.

Practical Significance Of The Research

The results obtained in this dissertation can be highly valuable for radar data processing, determining crustal deformations, and assessing the impact of oil and gas field development. In particular, the developed methods and software-algorithmic complex can be applied for:

• Identifying land subsidence, including in oil field areas.

• Planning and maintaining infrastructure. The use of land subsidence data in infrastructure development projects enables decision-making during construction in high-risk zones and determining measures to protect existing infrastructure from potential damage caused by surface deformations.

• Developing sustainable management strategies that balance resource extraction with minimal environmental impact. The research highlights the relationship between land surface deformation and oil and gas production, groundwater extraction, and natural compaction processes.

• Environmental management, land resource management, and resource extraction industries. Several key practical aspects stand out from this research.

• Development of action plans for emergency situations related to ground movement.

Theoretical significance of the research

The theoretical significance of the research results lies in their foundational contribution to advancing scientific knowledge and methodologies related to land surface movement analysis in oil and gas fields. These findings have the potential to significantly enhance current scientific studies by providing a robust framework for understanding and predicting ground deformation processes. Through this improved understanding, the research can aid in refining the technological approaches used to monitor such movements, which is critical for anticipating and mitigating potential environmental and operational risks in oil and gas extraction areas.Furthermore, by improving the accuracy and reliability of monitoring technologies, this research fosters the development of more sophisticated algorithms and data processing techniques. These enhancements not only support more precise detection and measurement of land surface shifts but also contribute to the predictive modeling capabilities essential for long-term resource management and sustainability. Thus, the theoretical insights gained from this research extend beyond immediate practical applications, offering a valuable scientific basis for future studies in geotechnical monitoring, environmental protection, and the responsible management of subsurface resources.

Methodology and Research Methods

This research utilizes a geospatial and temporal analysis approach to examine land displacement patterns across four key oil and gas fields in Kern County, California: North Belridge, South Belridge, Midway-Sunset, and Lost Hills-Belridge. To accomplish this, the study will rely on the following methodological steps:

1. Data Acquisition and Preprocessing:Sentinel-1 Synthetic Aperture Radar (SAR) data spanning from 2014 to 2023 will be acquired. SAR data offers detailed insights into surface deformation over large areas and extended timeframes, making it suitable for monitoring land displacement in oil and gas fields. The SAR data will be preprocessed using the Comet Portal, a tool designed for accessing, processing, and analyzing SAR data efficiently, and the LiCSBAS toolbox, which is specialized in interferometric synthetic aperture radar (InSAR) processing. These tools will ensure that the SAR data is prepared for accurate and efficient analysis of land displacement.

2. SBAS-InSAR Technique for Deformation Analysis:The Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) technique will be applied to the preprocessed SAR data. SBAS-InSAR is particularly effective for detecting gradual surface deformations by generating high-resolution deformation maps and time-series displacement graphs. This technique will allow for detailed observation of land displacement patterns across the four study fields, providing both spatial and temporal insights into ground movement.

3. Analysis of Spatial and Temporal Displacement Patterns :Using the generated deformation maps and time-series graphs, spatial and temporal patterns of land displacement will be identified and analyzed. This analysis will reveal trends, rates, and any significant anomalies in land movement across the study period, allowing for a nuanced understanding of displacement behavior in each oil and gas field.

4. Identification of Potential Causes :To interpret the causes of observed land displacement patterns, a literature review of existing studies on subsurface processes, fluid extraction, and geological characteristics will be conducted. Field visits will also be included, where feasible, to gather observational data and validate findings. This dual approach of literature review and field verification will enhance the study's accuracy in attributing displacement causes, considering factors such as fluid withdrawal, geological composition, and infrastructure development.

5. Evaluation of the SBAS-InSAR Technique:The study will also assess the effectiveness and limitations of the SBAS-InSAR technique based on the results obtained. Challenges such as data gaps, temporal decorrelation, or limitations in spatial resolution will be documented. This evaluation will provide insights into the robustness and limitations of SBAS-InSAR in detecting land deformation, especially in dynamic environments like oil and gas fields.

Through these methodological steps, the research will deliver a comprehensive analysis of land

displacement in Kern County's oil and gas fields, while critically evaluating the tools and techniques employed for geospatial monitoring. This approach not only addresses the research objectives but also contributes to improving methodologies for long-term environmental monitoring in resource extraction areas.

Main Provisions Submitted for Defense

This research will focus on four oil and gas fields in Kern County, California: North Belridge, South Belridge, Midway-Sunset, and Lost Hills-Belridge. Sentinel-1 SAR data between 2014 and 2023 will be acquired and preprocessed using Comet Portal and Liscbas toolbox. SBAS-InSAR technique will be applied to generate deformation maps and time-series displacement graphs. Spatial and temporal patterns of land displacement will be analyzed and potential causes will be identified through literature review and field visits. The limitations and challenges of SBAS-InSAR technique will be evaluated based on the results of the study.

• A method for processing Interferometric Synthetic Aperture Radar (InSAR) data to determine crustal mobility in oil and gas field areas.

• A method for processing radar data using SBAS-InSAR (Small Baseline Subset InSAR) with the Small Baseline Subset (SBAS) technique, which enables the detection and measurement of land displacement over time.

• A methodology for processing InSAR time series using extended interferograms and coherence analysis.

• A software package that facilitates the processing of InSAR data, enabling the creation of high-quality displacement maps for various time periods.

Degree of reliability of the results

The developed models are based on verified facts and data, consistent with published experimental and theoretical results on the dissertation topic.Commonly accepted optimization and modeling methods based on theories that have proven their applicability were used.The results of radar image processing were validated with ground-based data, based on GPS measurements. The quality and quantitative alignment of the author's results with those presented in independent sources on the topic have been confirmed.

Thesis Outline

This thesis is structured as follows: Chapter 1 presents a literature review of existing research on the impact of technology on modern society. Chapter 2 describes the research methodology used in the study, including the data collection and analysis methods. Chapter 3 presents the findings of the study, including an analysis of the impact of technology on culture, politics, and the economy. Finally, provides a summary of the research findings, conclusions, and recommendations for future research.

Заключение диссертации по теме «Другие cпециальности», Хатамиафкуиех Джавад

Summary of Findings

The results of this study indicate that InSAR can be an effective tool for monitoring land displacement in oil fields. The analysis of the Sentinel-1 data revealed significant land subsidence and uplift in all four oil fields. The patterns of land displacement were found to be different among the oil fields, with the South Belridge oil field experiencing the most severe subsidence. Time-series analysis showed that the land displacement rates varied over time, with some periods of faster subsidence or uplift.Based on the decomposition of the ascending and descending data, it was observed that the land displacement is primarily driven by the natural compaction of the reservoirs due to the extraction of oil and water. Other potential factors such as water injection, geological structures, and faults were also considered as possible contributors to the observed land displacement.

Contributions to the Field

This study contributes to the field of land displacement monitoring in several ways. First, it provides evidence of the effectiveness of InSAR for detecting and monitoring land displacement in oil fields. Second, it highlights the importance of conducting time-series analysis to understand the temporal variations of land displacement rates. Third, it identifies the potential causes of land displacement in oil fields and provides insights into the complex geomechanical processes that lead to land subsidence and uplift.In summary, the study utilized SBAS-InSAR technique to investigate the land displacement patterns in four major oil fields in Kern County, California. The results showed that all four oil fields experienced land subsidence and/or uplift, with the highest rates of subsidence observed in the North Belridge Oil Field and the highest rates of uplift observed in the Midway-Sunset Oil Field. Time series analysis revealed the presence of both seasonal and long-term trends in land displacement. The study also identified potential causes of land displacement, including oil and gas extraction, water injection, and natural compaction of sedimentary deposits.The comparison of different oil fields showed that land displacement patterns varied depending on the geological and hydrological characteristics of each field. The findings of this study are consistent with previous research on land displacement in oil and gas

fields, but also provide more detailed and up-to-date information on the magnitude and spatiotemporal variability of land displacement in Kern County, California.The study contributes to the field of land displacement monitoring by demonstrating the effectiveness of SBAS-InSAR for identifying and quantifying land displacement in complex geological and hydrological settings. The findings of this study can inform land use planning and decision-making in the oil and gas industry, as well as facilitate the development of effective mitigation and management strategies for land subsidence and/or uplift.However, the study has several limitations, including the limited spatial coverage of Sentinel-1 data and the lack of ground truth measurements for validation. As a result, future research should aim to enhance the accuracy and reliability of InSAR measurements by integrating data from multiple satellite sources along with ground-based observations.

Limitations and Future Research

There are several limitations to this study that should be addressed in future research. One limitation is the spatial resolution of the InSAR data, which may not be sufficient to capture localized land displacement patterns. Another limitation is the lack of ground truth data, which makes it difficult to determine the exact causes of the displacement. Future research should aim to address these limitations by using higher-resolution data and incorporating ground-based measurements.

Overall, this study demonstrates the potential of InSAR as a tool for monitoring land displacement in oil and gas fields. While there are limitations to the method, the results provide valuable insights into the impacts of oil and gas production on the surrounding land and can inform management and regulatory decision-making.

Recommendations for Future Research

Although this study provides valuable insights into land displacement in oil fields using InSAR, several limitations and avenues for future research should be considered. First, further research is needed to investigate the accuracy and precision of InSAR measurements in oil fields, particularly in areas with complex geological structures. Second, additional factors such as soil properties and hydrological conditions should be considered to develop more accurate models for predicting land displacement. Third, more comprehensive studies are needed to assess the environmental and socioeconomic impacts of land displacement in oil fields.

In conclusion, this study demonstrates the potential of InSAR for monitoring land displacement in oil fields and provides insights into the complex geomechanical processes that lead to land subsidence and uplift. The findings of this study can be useful for the oil and gas industry to develop more effective strategies for managing land subsidence and mitigating its potential impacts.In terms of limitations, this study was limited to analyzing only the North Belridge, South Belridge, Midway-Sunset, and Lost Hills-Belridge oil fields in Kern County, California. Therefore, the findings may not be generalizable to other oil and gas fields in different regions. Furthermore, the study only used data from Sentinel-1, and other

data sources such as aerial photography, GPS, and ground-based measurements were not included, which may have provided additional insights into the causes of land displacement. Additionally, the study did not consider the impact of human activity, such as infrastructure development and groundwater extraction, on land displacement.Future research in this area could focus on expanding the analysis to include more oil and gas fields in different regions to provide a more comprehensive understanding of land displacement patterns. Additionally, combining data from different sources, such as Sentinel-1 and GPS, could provide a more accurate measurement of land displacement.

Список литературы диссертационного исследования кандидат наук Хатамиафкуиех Джавад, 2024 год

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