Interferometric Synthetic Aperture Radar Monitoring Research Articles

Triggering of Land Subsidence in and Surrounding the Hangjiahu Plain Based on Interferometric Synthetic Aperture Radar Monitoring

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction.

An Interferometric-Synthetic-Aperture-Radar-Based Method for Predicting Long-Term Land Subsidence in Goafs through the Concatenation of Multiple Sources of Short-Term Monitoring Data

The land subsidence occurring over a goaf area after coal mining is a protracted process. The accurate prediction of long-term land subsidence over goaf areas relies heavily on the availability of long-term land subsidence monitoring data. However, the scarcity of continuous long-term land subsidence monitoring data subsequent to the cessation of mining significantly hinders the accurate prediction of long-term land subsidence in goafs. To address this challenge, this study proposes an innovative method based on interferometric synthetic aperture radar (InSAR) for predicting long-term land subsidence of goafs following coal mining. The proposed method employs a concatenation approach that integrates multiple short-term monitoring data from different coal faces, each with distinct cessation times, into a cohesive and uniform long-term sequence by normalizing the subsidence rates. The method was verified using actual monitoring data from the Yangquan No. 2 mine in Shanxi Province, China. Initially, coal faces with the same shapes but varying cessation times were selected for analysis. Using InSAR monitoring data collected between June and December of 2016, the average subsidence rate corresponding to the duration after coal mining cessation on each coal face was back-calculated. Subsequently, a function relating subsidence rate to the duration after coal mining cessation was fitted to the data. Finally, the relationship between cumulative subsidence and the duration after coal mining cessation was derived by integrating the function. The results indicated that the relationship between subsidence rate and duration after coal mining cessation followed an exponential function for a given coal face, whereas the relationship between cumulative subsidence and duration after coal mining cessation conformed to the Knothe time function. Notably, after the cessation of coal mining, significant land subsidence persisted in the goaf of the Yangquan No. 2 mine for a duration ranging from 5 to 10 years. The cumulative subsidence curve along the long axis of the coal face ultimately exhibited an inclined W-shape. The proposed method enables the quantitative prediction of residual land subsidence in goafs, even in cases where continuous long-term land subsidence monitoring data are insufficient, thus providing valuable guidance for construction decisions above the goaf.

Sensitivity Evaluation of Time Series InSAR Monitoring Results for Landslide Detection

Spaceborne interferometric synthetic aperture radar (InSAR) techniques are important for landslide detection and monitoring; however, several limitations and uncertainties, such as the unique north–south flying direction and side-look radar observing geometry, currently limit the ability of InSAR to credibly detect landslides, especially those related to high and steep slopes. Here, we conducted experimental and statistical analysis on the feasibility of time-series InSAR monitoring for steep slopes using ascending and descending SAR images. First, the theoretical (TGNSS), practical (PGNSS), and terrain (Hterrain) (T-P-H) indices for sensitivity evaluations of the slope displacement monitoring results from time-series InSAR were proposed for slope monitoring. Subsequently, two experimental and statistical studies were conducted for the cases with and without Global Navigation Satellite System (GNSS) monitoring data. Our experimental results of two high and steep open-pit mines showed that the defined theoretical and practical sensitivity indices can quantitatively evaluate the feasibility of ascending and descending InSAR observations in steep-slope deformation monitoring with GNSS data, and the terrain sensitivity index can qualitatively evaluate the feasibility of landslide monitoring results from ascending and descending Sentinel-1 satellite data without GNSS data. We further demonstrate the generalizability of these proposed indices using four landslide cases with both public GNSS and InSAR monitoring data and 119 landslide cases with only InSAR monitoring data. The statistical results indicated that greater indices correlated with higher reliability of the monitoring results, suggesting that these novel indices have wide suitability and applicability. This study can help to improve the practice of slope deformation monitoring using spaceborne InSAR, especially for high and steep slopes.

A Case Study Integrating Numerical Simulation and InSAR Monitoring to Analyze Bedding-Controlled Landslide in Nanfen Open-Pit Mine

Bedding-controlled landslides are a common geological hazard for open-pit metal mines and occur on layered rock slopes. It can spread spatially over the final boundary of the dip slope and persist throughout the entire life cycle of the mine, substantially compromising the safety of mining operations. Identifying potential landslide areas and determining the landslide mechanism is crucial for the safety production and slope management of mines. This study proposes a combination of satellite radar interferometry measurement and numerical simulation to determine the landslide mechanism of the bedding-controlled slope in open-pit mines. First, the multidimensional small baseline subset (MSBAS) technique of interferometric synthetic aperture radar (InSAR) is used to capture deformation information in the vertical and east–west directions of the slope, locate large-scale and long-term movements, and preliminarily determine the trend of landslides. Then, a layered slope damage constitutive model is established, and a three-dimensional stability calculation of the layered slope is performed using COMSOL Multiphysics 5.3 software based on the strength reduction method to study the development and evolution process of landslides. The effectiveness of the method is validated by a large-scale bedding-controlled slope failure in the Nanfen open-pit mine in Liaoning, China, revealing the failure mechanism of the slope under excavation conditions. The study shows that the eastern slope bedding-controlled landslide in the Nanfen open-pit mine is a multizone composite-mode landslide caused by excavation, which belongs to the shear–slip–tension deformation failure mechanism as a whole. This study provides a new method for analyzing the mechanism of layered rock slope landslides under mining activities in open-pit mines, which can be used to assess and predict similar landslides.

Interferometric Synthetic Aperture Radar (InSAR) and field‐based observations of rainfall‐triggered landslides from the November 2021 storm, Gisborne/Tairāwhiti, New Zealand

AbstractGisborne/Tairāwhiti is particularly susceptible to rainfall‐triggered landslides on account of (1) steep slopes, (2) young, soft geology, (3) landuse change effects. The interplay of these factors led to a particularly damaging rainfall‐induced landsliding event during 3–7 November 2021, following >200 mm of rainfall. This caused a Multiple Occurrence Regional Landslide Event, impacting residential properties and infrastructure in the city and rural areas. We report mainly on landslides in Gisborne city and suburbs, based on field reconnaissance and interferometric synthetic aperture radar monitoring of slopes. This highlights prevailing land instability prior to the more recent ex‐Tropical Cyclone Gabrielle (2023).

Satellite remote sensing of UK embankment dams: influence of dam features on monitoring quality

Radar interferometry (interferometric synthetic aperture radar (InSAR)) is a satellite remote sensing technique, which offers deformation monitoring at frequent intervals with sub-centimetre accuracy. The most popular form of InSAR monitoring for infrastructure is persistent scatterer interferometry (PSI). This relies on the identification of persistent scatterers: permanent, rigid objects which can reliably backscatter a signal to the satellite receiver. As the typical UK embankment dam has grassed slopes, the majority of persistent scatterers are detected at hard infrastructure located at the dam crest. The aim of this paper is to study the influence of dam features on persistent scatterer detection and quality at Scottish Water embankment dams. Following a case study in which PSI can be shown to detect dam deformation associated with an extreme climate event (the summer 2018 heatwave), statistics from 17 Scottish embankment dams are used to determine which dam features lead to the best-quality PSI results. The type of wave protection at the crest of a dam is the biggest influence, whereas the presence of an asphalt-surfaced crest road is shown to have a surprisingly limited effect on persistent scatterer quality.

Research on time series InSAR monitoring method for multiple types of surface deformation in mining area

Interferometric Synthetic Aperture Radar (InSAR) has become the primary remote sensing detection method for monitoring significant surface subsidence and deformation caused by underground coal mining. Time Series InSAR has been intensively researched in mining-caused deformation monitoring for its ability to provide surface deformation time series, with Small Baseline Subset InSAR (SBAS-InSAR) and Permanent Scatter InSAR (PS-InSAR) being two classical methods. To obtain the incline and curvature in mining areas and assess the building damage, this paper exploits the SBAS-InSAR and PS-InSAR techniques to estimate surface incline and curvature, following the principle of directional derivatives. The surface beneath the villages and the industrial square near the 7221 Grout-filled working face in the Huaibei mining area of Anhui Province, China, was analyzed. The estimated surface incline and curvature with SBAS-InSAR were within the threshold values specified for Class I damage, while PS-InSAR showed <1% of measurements that exceeded this threshold. This paper provides a method for monitoring the surface deformation beneath the buildings in the mine area. Meanwhile, the dynamic analysis of the damaged buildings provides a basis for determining the influence range with grout-filled working faces.

Nationwide, Operational Sentinel-1 Based InSAR Monitoring System in the Cloud for Strategic Water Facilities in Hungary

The intensive development of both interferometric technology and sensors in recent years allows Interferometric Synthetic Aperture Radar (InSAR)-based applications to be accessible to a growing number of users. InSAR-based services now cover entire countries and soon even the whole of Europe. These InSAR systems require massive amounts of computer processing power and significant time to generate a final product. Most, if not all, of these projects have a limited “monitoring component”, aimed at historical analysis but are rarely, if ever, updated. Consequently, the results do not necessarily meet every purpose or specific user requirement. It is now clear that the increasing computing capacity and big data provided by the sensors have initiated the development of new InSAR services. However, these systems are only useful when linked to specific real-world operational problems. Continuous monitoring of a country’s ageing water management infrastructure has become an increasingly critical issue in recent years, in addition to the threats posed by climate change. Our article provides a comprehensive overview of a nationwide, dedicated, operational InSAR application, which was developed to support the operational work of the Hungarian Disaster Management Service (HDMS). The objective was to provide monthly monitoring of 63 water facilities, including 83 individual objects, distributed throughout Hungary, in combination with the development of a near real-time warning system. Our work involved the compilation of a completely new InSAR System as a Service (SaaS) which incorporates user requirements, preparatory work, the compilation of the Sentinel-1 automatic processing pipeline, the installation of corner reflectors, a special early warning system, and a dedicated user interface. The developed system can automatically start to evaluate the S1 measurements within 24 h of downloading the data into the system storage forward the results toward the warning system before the next image arrives. Users are provided with detailed information on the stability of 70% of the 83 water facility objects monitored through the dedicated user interface. The additional early warning system currently operates as a preliminary “spatial decision support system”, but the HDMS is willing to make it fully operational over the next few years.

Stability Evaluation of Massive Landslides Using Ensembled Analysis of Time-Series InSAR and Numerical Simulation along the Yellow River, Northwestern of China

Loess landslides are a major geological disaster in the southeastern Qinghai Province, causing huge economic losses and casualties. The particularity of loess determines the disaster initiation mechanism, disaster mode, genetic mechanism, and complexity of the evolution process. This paper studies the deformation and stability analysis of the Quwajiasa large-scale multislip loess landslide in the Yellow River Basin from the perspective of field investigation, Interferometric Synthetic Aperture Radar (InSAR) monitoring, and numerical simulation. This study determines the deformation characteristics and genetic mechanism of the landslide through on-site field investigation, then quantitatively evaluates the overall deformation of the landslide using InSAR monitoring, locates the strong deformation area, and finally determines the control relationship between the two sliding surfaces on the landslide deformation using FLAC3D numerical simulation, obtaining the stability coefficient of the two sliding surfaces. The landslide is divided into seven engineering geological zones. The deformation history of the landslide is studied using InSAR technology. Results show that the landslide can be divided into significant deformation areas and no significant deformation areas. Two strong deformation areas are found. The FLAC3D numerical simulation results show that the deformation and stability of the right side of landslide are controlled by sliding surface 1, and the deformation and stability of the left side are controlled by sliding surface 2. The landslide is in an unstable state overall. The research done in this paper proposes a basis for the treatment of the Quwajiasa landslide.

Comparison of in situ and interferometric synthetic aperture radar monitoring to assess bridge thermal expansion

Asset owners responsible for the management and maintenance of bridges value the collection of data that can be processed into useful information to inform decisions about future management of structures. Installing, powering and receiving data from sensors is not always convenient or possible, but satellite monitoring may provide the ability to measure bridge movements and thus provide an indication of potential problems for asset owners to take action on. This study presents the results of satellite monitoring of the Hammersmith flyover, London, UK, using the interferometric synthetic-aperture radar (InSAR) technique. Sentinel-1 (free) and Cosmo-SkyMed (commercial) satellite radar data were processed to provide millimetre-scale measurements of the flyover and surrounding region and validated with in situ sensor measurements. A method was developed for selecting and comparing InSAR measurements with in situ displacement and temperature measurements, making use of bridge geometrical and structural modelling information. The results compare in situ sensor measurements with remote InSAR measurements and show the suitability of such measurements in measuring thermal expansion for some (but not all) bridge assets. The proposed techniques, illustrated with the case study of the Hammersmith flyover, will enable asset owners to collect regular measurements of bridge movements to complement and add value to current inspection methods and potentially give early warning to defective bridge bearings.

Intra‐Annual Ground Surface Deformation Detected by Site Observation, Simulation and InSAR Monitoring in Permafrost Site of Xidatan, Qinghai‐Tibet Plateau

AbstractThe permafrost degradation can cause long‐term ground surface subsidence, and the surface undergoes frost heave and thaw settlement due to the ice‐water phase change in the active layer. The multi‐year surveys by leveling observations and Interferometric Synthetic Aperture Radar monitoring (InSAR) are helpful to understand the characteristics of seasonal deformation and to model the permafrost terrain surface deformation. In this paper, we studied the characteristics of seasonal deformation over permafrost terrain in Xidatan, obtained by leveling measurements from 2010 to 2018, Sentinel‐1 data from 2014 to 2020, and hydrothermal‐data‐based simulation. The results consistently showed a four‐stage pattern of seasonal deformation characteristics: Summer thaw subsiding, warm‐season stable‐standing, winter freeze heaving and stable‐standing. The leveling measurements proved that spatial heterogeneity also exists on a small spatial scale (400 m2). The deformation amplitude obtained by leveling data is the largest, and the InSAR data is the smallest.

Proving compliance of satellite InSAR technology with geotechnical design codes

In the planning stage of new infrastructure or when designing renovation of existing infrastructure, information about existing slope movements or settlements is essential to make informed design decisions. Interferometric Synthetic Aperture Radar (InSAR) techniques can be of value to identify these risks in an early stage of a project. InSAR can offer insight into the surface movements of an area from historic archives using satellite-based SAR data. Furthermore, InSAR observations can help identify zones with displacements larger than the average of an area, and be used to plan future soil investigation more effectively. Thanks to their high temporal and spatial resolution, InSAR observations can also complement in situ conventional monitoring during the construction and operational stage. Despite these possibilities, the use of InSAR is not yet standard practice in geotechnical projects and no formal guidelines are currently available to inform engineers, planners and infrastructure stakeholder on the use of InSAR-based monitoring within geotechnical design codes. Here we provide an operational framework for the practical integration of InSAR monitoring into current geotechnical design codes, such as Eurocode-7, for all project stages. The proposed framework is then demonstrated for the planning stage of a highway renovation project, focusing on an area potentially subjected to landslides where no conventional monitoring data was available at this stage. We concluded that the proposed framework is a practical and operational tool that can be used by planners and engineers in the whole lifecycle of an infrastructure project.

Analysis of Available Conditions for InSAR Surface Deformation Monitoring in CCS Projects

Carbon neutrality is a goal the world is striving to achieve in the context of global warming. Carbon capture and storage (CCS) has received extensive attention as an effective method to reduce carbon dioxide (CO2) in the atmosphere. What follows is the migration pathway and leakage monitoring after CO2 injection. Interferometric synthetic aperture radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCS projects. However, there is no mature evaluation system to determine whether InSAR technology is suitable for each CO2 sequestration area. In this study, a new evaluation model is proposed based on the eight factors that are selected from the principle of the InSAR technique and the unique characteristics of the CO2 sequestration area. According to the proposed model, the feasibility of InSAR monitoring is evaluated for the existing typical sequestration areas in the world. Finally, the challenges and prospects of InSAR in the CCS project are discussed.

Ascending and Descending Time Series Interferometric Synthetic Aperture Radar Monitoring and Analysis of Landslide Deformation

Ascending and Descending Time Series Interferometric Synthetic Aperture Radar Monitoring and Analysis of Landslide Deformation

Dynamic Estimation of Multi-Dimensional Deformation Time Series From InSAR Based on Kalman Filter and Strain Model

With the increasing amount of synthetic aperture radar (SAR) data with various imaging geometries (at least ascending/descending tracks), it is possible to obtain accurate multi-dimensional (MD) deformation time series with long time span. However, in most cases SAR data of different geometries are un-synchronously acquired over the same region, making it impossible to directly solve the underdetermined observation model (OSM) between the interferometric SAR (InSAR) measurements and the MD deformations. Kalman filter (KF), as one of the most famous dynamic estimators, can obtain <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> information of the unknowns based on the preexisting time series, therefore it can be used to deal with this InSAR underdetermined problem. This article employs the KF to realize the dynamic estimation of MD deformations with short-baseline interferograms. The innovation lies in the establishment of the KF state transition model (STM) and OSM, which aims to make the InSAR monitoring problem better adapt to the KF. Particularly, by assuming a smooth deforming process, existing deformation time series are used to establish the STM and to predict the deformations at current moment. Besides, a strain model (SM) is employed to assist the establishment of the OSM. Simulation and real experiments in the Geysers geothermal field (GGF), U.S. demonstrate that, compared with the state-of-the-art methods, the proposed KF method allows more robust deformation estimation and achieves higher computational efficiency for dynamic estimation.

Atmospheric phase delay correction of PS-InSAR to Monitor Land Subsidence in Surabaya

Atmospheric phase delay is one of the most significant errors limiting the accuracy of Interferometric Synthetic Aperture Radar (InSAR) results. In this research, we used the Generic Atmospheric Correction Online Service for InSAR (GACOS) data to correct the tropospheric delay modeling from the persistent scatterers’ InSAR monitoring. Eighty-one (81) Sentinel-1A images and tropospheric delay maps from GACOS monitored land subsidence in Surabaya city between 2017 and 2019. InSAR processing was carried out using the GMTSAR software, continued with StaMPS and TRAIN, which were used to correct the tropospheric delay of PSInSAR-derived deformation measurements. The results before and after the atmospheric phase delay correction using GACOS were confirmed and analyzed in the main subsidence area. The findings of the experiments reveal that the atmospheric phase affects the mean LOS velocity results to some extent. The average difference between PS-InSAR before and after tropospheric correction is 1.734 mm/year with a standard deviation of 0.550 mm/year. The significance test of the two variables, 95%, showed that the tropospheric correction with GACOS data could affect the PS-InSAR results. Furthermore, GACOS correction may increase the error at some points, which could be due to its turbulence data’s low accuracy.

InSAR monitoring data to assess building response to deep excavations

Recently, there has been growing interest to use Interferometric Synthetic Aperture Radar (InSAR) to quantify ground displacements. While InSAR can well determine the area and magnitude of subsidence, very little attention has been paid to explore InSAR measurements to assess the building response adjacent to geotechnical works (e.g., deep excavations, tunnelling). Specifically, few studies have investigated the ability of using InSAR to derive widely accepted building deformation parameters including angular distortion and horizontal strain. On the other hand, geotechnical engineers generally use traditional monitoring data to assess the behaviour of existing structures adjacent to excavations, but often only spatially and temporally limited monitoring data exist to reliably evaluate the governing mechanisms. This contribution follows a case study approach to explore the value of InSAR to quantify the effects of excavation-induced settlements on buildings. Conventional monitoring data of structures adjacent to excavation works for a construction project in Oslo, Norway, are compared to InSAR measurements from satellites with different spatial resolutions and from two different processing methods. Differences between displacements obtained from these different InSAR monitoring datasets and their practical implementation are discussed. Building deformations and respective damage categories are then quantified using a methodology that combines both InSAR and inclinometer measurements. As expected, it was found that high resolution InSAR measurements are more reliable when assessing the building response to excavation works.

InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California

Monitoring surface deformation associated with geohazards is a prerequisite for geological disaster prevention. Interferometric synthetic aperture radar (InSAR) has the ability to capture ground deformation of landslides with high precision over a large area. However, in mountainous regions this capability is often limited by decorrelation noise and atmospheric phase artifacts. Over Eldorado National Forest, California, where many landslides need to be monitored and investigated, InSAR images are severely affected by atmospheric noise and the coherence is highly variable throughout the year, challenging InSAR techniques to effectively detect movement of active landslides. In order to obtain reliable measurements, we have designed an interferogram selection method and an InSAR segment processing (SP) technique to improve the deformation measurement. Compared with the traditional non-segment processing (NSP), the SP technique has demonstrated advantages in reducing the impact of atmospheric noise. Our results from both the ascending and descending InSAR datasets based on SP indicate that many landslides along the Highway 50 corridor were creeping at a rate of less than 10 cm/year during the investigation period. We have found that landslide movements in the study region present obvious seasonal patterns. The precipitation and pore-water measurements and our hydrogeological diffusion models suggest that the seasonal movements of these landslides are primarily driven by the pore-water pressures, and the peak deformation of the landslides may occur in the dry season (May to October) due to the time lag of precipitation infiltration. In addition, we have observed subtle upward movement of the landslides after the precipitation begins, which is likely caused by the swelling of clay-rich landslide body due to an increase in the pore pressure. Furthermore, several other localized unstable regions which may contain potential landslide hazards were also detected and mapped in the study area, and their dynamics need further investigation. We conclude that InSAR is capable of detecting slow landslide motions over difficult terrains if associated artifacts in the interferograms are suppressed. InSAR time-series measurements along with hydrogeological models enable us to characterize the time delay between peaks of landslide motions and precipitation.

InSAR Monitoring of Landslide Activity in Dominica

Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.

Assessing mechanical response of CO2 storage into a depleted carbonate reef using a site-scale geomechanical model calibrated with field tests and InSAR monitoring data

Geomechanical risks of injection have raised concerns regarding secure CO2 storage. In this work, a combined monitoring and modeling approach is used to assess the stress changes and surface uplift associated with CO2 injection into a depleted carbonate reef of the Michigan basin. A site-scale geomechanical model is built by assigning mechanical properties of formations using well-log and experimental data. Gravity load is applied to the model to estimate the vertical component of stress as well as different lateral boundary displacement scenarios to estimate horizontal stresses. We used a poroelastic pressure-dependent model (instead of a linear elastic mechanical earth model) to calibrate initial stresses using hydraulic fracture test data measured at depleted reservoir status. Multi-phase fluid flow-geomechanical simulations are performed to estimate the poroelastic response during (1) primary depletion (2) field-scale CO2 injection phase (3) a hypothetical forecast scenario in which well bottom hole pressure (BHP) reach 45000 KPa. The predicted surface uplift is less than 1 mm at the end of the field-scale CO2 injection phase which is in good agreement with Interferometric Synthetic Aperture Radar (InSAR) uplift measurement. Although the InSAR data shows an insignificant uplift, hydromechanical modeling of injection shows that CO2 injection still causes reservoir deformation emphasizing the role of carbonate overburden and reservoir formation mechanical properties and limited size of reef on diminishing the surface deformation. Modeling indicates poroelastic response of caprock matters to estimate uplift. The lower permeability of the top two layers provides additional barrier to large uplift. Also, history of subsidence due to production should be accounted to predict uplift due to a follow up injection correctly. This study shows the significance of combining a calibrated geomechanical model with field measured stresses and monitoring data to be used as a tool to ensure the safety of CO2 storage.