The state of the art in monitoring and verification— ten years on

In the ten years since publication of the IPCC Special Report on CCS, there has been considerable progress in monitoring and verification (M&V). Numerous injection projects, ranging from small injection pilots to much larger longer-term commercial operations, have been successfully monitored to the satisfaction of regulatory agencies, and technologies have been adapted and implemented to demonstrate containment, conformance, and no environmental impact. In this review we consider M&V chiefly from the perspective of its ability to satisfy stakeholders that these three key requirements are being met. From selected project examples, we show how this was done, and reflect particularly on the nature of the verification process. It is clear that deep-focussed monitoring will deliver the primary requirement to demonstrate conformance and containment and to provide early warning of any deviations from predicted storage behaviour. Progress in seismic imaging, especially offshore, and the remarkable results with InSAR from In Salah are highlights of the past decade. A wide range of shallow monitoring techniques has been tested at many sites, focussing especially on the monitoring of soil gas and groundwater. Quantification of any detected emissions would be required in some jurisdictions to satisfy carbon mitigation targets in the event of leakage to surface: however, given the likely high security of foreseeable storage sites, we suggest that shallow monitoring should focus mainly on assuring against environmental impacts. This reflects the low risk profile of well selected and well operated storage sites and recognizes the over-arching need for monitoring to be directed to specific, measureable risks. In particular, regulatory compliance might usefully involve clearer articulation of leakage scenarios, with this specificity making it possible to demonstrate “no leakage” in a more objective way than is currently the case. We also consider the monitoring issues for CO2-EOR, and argue that there are few technical problems in providing assurance that EOR sites are successfully sequestering CO2; the issues lie largely in linking existing oil and gas regulations to new greenhouse gas policy. We foresee that, overall, monitoring technologies will continue to benefit from synergies with oil and gas operations, but that the distinctive regulatory and certification environments for CCS may pose new questions. Overall, while there is clearly scope for technical improvements, more clearly posed requirements, and better communication of monitoring results, we reiterate that this has been a decade of significant achievement that leaves monitoring and verification well placed to serve the wider CCS enterprise

\textsc{DeFault}: Deep-learning-based Fault Delineation

The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection serve as indispensable tools, offering vital insights into subsurface structures and fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high-quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, DeFault, specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain-adaptation, DeFault allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using DeFault, the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of DeFault on a field case study involving CO2 injection related microseismic data from the Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and aided in the prevention of potential geological hazards. Our results highlight the potential of DeFault as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning's capacity to refine these methods. Ultimately, our work bear significant implications for CCUS technology deployment, an essential strategy in combating climate change

Advanced Analysis of Time-lapse Seismic Data for CO2 Geosequestration Monitoring

This thesis addresses challenges of land time-lapse (4D) surface seismic data analysis for monitoring of CO2 geosequstration. The approach includes development of an optimal seismic acquisition strategy, seismic forward modelling workflow, model-guided processing and imaging of the 4D seismic data for structural and quantitative interpretation. Successful onshore seismic monitoring is achieved using buried geophone array and purposefully designed processing flow with tracking of 4D signal and noise at each processing stage

Land seismic repeatability prediction from near-surface investigations at Naylor Field, Otway

Time-lapse seismic is a powerful methodology for remotely monitoring changes in oil and gas reservoirs. Its high sensitivity and resolving power make it the methodology of choice for monitoring CO2 sequestration in deep saline aquifers or depleted oil and gas fields. This method is now routinely applied offshore but rarely onshore because of inherently poor repeatability of land seismic data. Considering that CO2 sequestration on land is becoming a necessity, there is a great need to evaluate the feasibility of this method for land based CO2 sequestration projects. A feasibility study, onshore Otway Basin, Australia, aims at evaluating the viability of monitoring methodologies for the case of CO2 storage into a depleted gas field. Since injection of CO2 into a depleted gas field at a depth of around 2 km causes very subtle changes in elastic properties of the reservoir rock, it is critical to achieve high repeatability of time-lapse seismic surveys if they are to be implemented into a monitoring program.The goal of this thesis is to analyse the main factors affecting seismic repeatability at the Otway site. I aim to achieve this goal through the deployment of pre-base line measurements and combining the results with detailed numerical modelling studies. Such measurements have to be rapid, effective and quantitative so that a seismic monitoring team can decide whether to use time-lapse methodology when processing their data.To find the most likely repeatability at the Otway site I used so-called micro-arrays (surface and borehole) in a time-lapse manner to determine the seasonal variation of elastic properties of the near surface. The measurements were aimed at determining directional P-wave velocity and attenuation (Q-factor). The top soil (0.5m thick agricultural layer or elasto-plastic zone) had a low velocity and low Qfactor and hence significantly attenuated seismic energy.The elastic parameters obtained were then used to numerically simulate real timelapse surveys. The results obtained were compared and verified against conventional time-lapse studies conducted at the Otway site over a three year period, at different times of the year and with different sources. The agreement between numerical and field data, expressed through a normalised root mean square (NRMS) difference confirms that the effect of the near surface variation in the time-lapse land seismic can be predicted with minimum cost and through the deployment of small, inexpensive experiments

Subsurface Imaging and Petrophysical Analysis of the South Georgia Rift Basin, South Carolina

The Triassic-Jurassic South Georgia Rift (SGR) basin, buried beneath Coastal Plain sediments of southern South Carolina, southeastern Georgia, western Florida, and southern Alabama, consists of an assemblage of continental rift deposits (popularly called red beds), and mafic igneous rocks (basalt flows and diabase sills). The red beds are capped by basalts and/or diabase sills, and constitute the target for supercritical CO2 storage as part of a Department of Energy funded project to study feasibility for safe and long-term sequestration. This study addresses key stratigraphic, structural and petrophysical issues critical to determine subsurface suitability for CO2 storage as well as improved understanding of the Triassic basin\u27s evolution and underline characteristics. Also unlike shale-capped CO2 reservoirs, very little is known about the ability of basalts and diabase sills to act as viable seals for CO2 storage. New interpretations from reprocessed SeisData6 Coastal Plain, supported by analysis of well data, substantiate the presence of a buried Triassic basin in South East Georgia that is about 2.2 km deep and 170 km wide. It appears to coincide with the subsurface convergence of the southwest and northeast extensions of the Riddleville and Dunbarton basins that are subsidiaries of the main SGR basin. Contrary to previous study, this basin does not have basalt. Our data show no clear evidence for the Augusta fault that was identified in other studies in the vicinity of the Piedmont-Coastal Plain boundary in Georgia and South Carolina. Petrophysically, the SGR basin manifests distinct porosity-permeability regimes that are influenced by the depositional environments. New results also indicate the presence of thick, confined porous red beds with average porosity as high as 14%. However, the red beds\u27 permeability is generally low and shows large numerical variations both locally and regionally. Low permeability is caused by poor sorting, small pore throats and tectonically induced compaction and diagenesis. Changes in porosity and permeability with depth are highly significant within the SGR basin, and suggest a compacted basin with a history of uplift and erosion. Analyses further show that the basalt flows and diabase sills in the southern South Carolina part of the SGR possess low porosity, high seismic velocity, and density that are favorable to caprock integrity

TRA of DigiMon components

The DigiMon project aims to develop an affordable, flexible, societally embedded and smart monitoring system for industrial scale subsurface CO2 storage. For this purpose, the DigiMon system is to combine various types of measurements in integrated workflows. In this report, we describe the process of conducting the Technology Readiness Assessment (TRA) of various measurement techniques. We report on the identification, description and assessment of these measurement techniques as Critical Technology Elements (CTEs) being part of the DigiMon system

Deliverable 4.6 Design of multi-site and multi-scale monitoring schemes

This report describes a monitoring scheme applicable for CO2 storage projects at different maturity levels and scales. It is the final delivery from ACT SHARP (“Accelerating CCS Technologies - Stress history and reservoir pressure for improved quantification of CO2 storage containment risks”) Work package 4 (WP4) – “Monitoring”. It builds on previous deliveries from WP4 and other SHARP work packages on multi-scale geomechanical rock failure risks (both onshore and offshore), machine-learning approaches for seismicity detection, and optimal use of fibre optics. In this report we introduce the concept of Geomechanical Readiness Level (GRL), a scale intended to help storage operators evaluate the readiness of their potential injection site with respect to available data characterising the stress conditions at the site. We discuss how selected potential storage sites in the North Sea and onshore India place in the GRL scale, and how work performed both within SHARP and by individual operators has matured each site to their present GRL level. We also present an overview of monitoring tools for detecting geomechanical pore pressure and stress changes and discuss their different applications. The focus in SHARP has especially been on potential fibre optics applications, which have the potential to detect a variety of subsurface changes (pressure, temperature, seismic responses, strain), but which also comes with limitations (directivity, deployment limitations, noise, handling large data volumes). An important delivery from WP4 has been developing efficient data analysis tools, capable of combining observations from different sources and handling large datasets with machine learning. Finally, we describe how an optimal monitoring programme needs to be tailored to the site(s) in question, selecting optimised monitoring tools depending on the relevant risks and geomechanical setting.European CommissionpublishedVersio