Project report with guidelines and recommendations for a monitoring system to be applied at a set of planned or active CCS sites

Project report with guidelines and recommendations for a monitoring system to be applied at a set of planned or active CCS sites.publishedVersio

Improved algorithms to acquire and process gravity and deformation data

The work presented in this deliverable is part of the efforts to meet the following sub-objectives of the DigiMon project: • Prepare for integration of DigiMon system by developing and lifting individual components of the system to a common, high TRL. • Secure optimal performance of the DigiMon system by optimization and validation of processing software for DigiMon system components • Develop and implement efficient techniques for data acquisition and processing of gravity, seafloor deformation and seismic data. More specifically, deliverable D2.1 summarizes contributions to the development of two individual technologies, microgravity at the seafloor and seafloor deformation monitoring for applications within CCS. In total, four individual developments are described in this deliverable. The developments contribute to reducing the cost of gravimetry and seafloor deformation monitoring to make them more feasible for CO2 sequestration applications, which are more price-sensitive than for the case of oil and gas. In addition, they aim at improving the accuracy of the data to facilitate refined quantitative estimates of the properties of the storage unit and improve CCS management

Comparing Risk Perceptions and Risk Management in Organic and Conventional Dairy Farming: Empirical Results From Norway

This study was conducted to explore organic and conventional dairy farmers' perceptions of risk and risk management, and to examine relationships between farm and farmer characteristics, risk perceptions, and strategies. The data originate from a survey of conventional (n=363) and organic (n=162) dairy farmers in Norway. Organic farmers had the least risk averse perceptions. Institutional and production risks were perceived as primary sources of risk, with farm support payments at the top. Compared to their conventional colleagues, organic farmers gave more weight to institutional factors related to their production systems. Conventional farmers were more concerned about costs of purchased inputs and animal welfare policy. Organic and conventional farmers' management responses were more similar than their risk perceptions. Financial measures such as liquidity and costs of production, disease prevention, and insurance were perceived as important ways to handle risk. Even though perceptions were highly farmer-specific, a number of socio-economic variables were found to be related to risk and risk management. The primary role of institutional risks implies that policy makers should be cautious about changing policy capriciously and they should consider the scope for strategic policy initiatives that give farmers some greater confidence about the longer term. Further, researchers should pay more attention to institutional risks

Risk and Risk Management in Organic and Conventional Dairy Farming: Empirical Results from Norway

The objective of this study was to provide empirical insight into dairy farmers' goals, relative risk attitude, sources of risk and risk management responses. The study also examines whether organic dairy farming, leads to important risk sources not experienced in conventional farming and, if so, how those extra risks is managed. The data originate from a questionnaire survey of conventional (n=370) and organic (n=160) dairy farmers in Norway. The results show that organic farmers have somewhat different goals than conventional farmers, and that the average organic farmer is less risk averse. Institutional risk was perceived as the most important source of risk, independently of conventional or organic production system, while organic farmers indicated greater concern about forage yield risk. Keeping cash on hand was the most important strategy to manage risk for all dairy farmers. Diversification and different kinds of flexibility was regarded as a more important risk management strategies among organic than conventional farmers.Livestock Production/Industries, Risk and Uncertainty,

Project report and algorithms for optimizing acquisition layout and frequency

D2.7. Project report and algorithms for optimizing acquisition layout and frequency. We evaluate the capability of 3D finite difference codes to model Distributed Acoustic Sensors (DAS) at reservoir scale for monitoring of CO2 sequestration. This work builds on previous DigiMon deliverables: 1.3 - DAS synthetic dataset (Baird et al, 2020b) and 2.1 - Framework for forward modelling of the DigiMon data (Vandeweijer et al, 2021). The goals of this work include 1) evaluation of the computational load and trade-offs needed to model Distributed Acoustic Sensing (DAS) signals from a 3D (~14x14x3 km) model of a CO2 sequestration reservoir; 2) sensitivity of various DAS deployment models (borehole versus surface); 3) comparison of DAS (linear and helical) with respect to geophones for both vertical and surface installations; and 4) measurements of possible induced seismicity with DAS

Electrical conductivity of fractured media: A computational study of the self-consistent method

Effective medium theory can be used to link conductivity estimation methods with prior knowledge about the distribution of fractures in the investigated geological structure. In the literature, little work has been presented on assessing the accuracy of effective medium approximations for dense networks of finite-sized fractures. We present here a systematic computational study, comparing the conductivity predictions of the popular self-consistent method with results from numerical finite-element simulations. Our results show that the selfconsistent method is accurate within acceptable error bounds for a range of parameter values, in some cases even beyond the percolation limit. We also compare the percolation thresholds predicted by self-consistent theory with the thresholds obtained by a numerical percolation algorithm. For the cases we have studied, the percolation thresholds agree to a remarkable degree.acceptedVersio

A 3D computational study of effective medium methods applied to fractured media

This work evaluates and improves upon existing effective medium methods for permeability upscaling in fractured media. Specifically, we are concerned with the asymmetric self-consistent, symmetric self-consistent, and differential methods. In effective medium theory, inhomogeneity is modeled as ellipsoidal inclusions embedded in the rock matrix. Fractured media correspond to the limiting case of flat ellipsoids, for which we derive a novel set of simplified formulas. The new formulas have improved numerical stability properties, and require a smaller number of input parameters. To assess their accuracy, we compare the analytical permeability predictions with three-dimensional finite-element simulations. We also compare the results with a semi-analytical method based on percolation theory and curve-fitting, which represents an alternative upscaling approach. A large number of cases is considered, with varying fracture aperture, density, matrix/fracture permeability contrast, orientation, shape, and number of fracture sets. The differential method is seen to be the best choice for sealed fractures and thin open fractures. For high-permeable, connected fractures, the semi-analytical method provides the best fit to the numerical data, whereas the differential method breaks down. The two self-consistent methods can be used for both unconnected and connected fractures, although the asymmetric method is somewhat unreliable for sealed fractures. For open fractures, the symmetric method is generally the more accurate for moderate fracture densities, but only the asymmetric method is seen to have correct asymptotic behavior. The asymmetric method is also surprisingly accurate at predicting percolation thresholds.acceptedVersio

DigiMon Final Report

"DigiMon Final Report” summarizes the ACT DigiMon project. The overall objective of the DigiMon project was to “accelerate the implementation of CCS by developing and demonstrating an affordable, flexible, societally embedded and smart Digital Monitoring early-warning system”, for monitoring any CO2 storage reservoir and subsurface barrier system, receiving CO2 from fossil fuel power plants, oil refineries, process plants and other industries.DigiMon Final ReportpublishedVersio

Project report and algorithms for integrated inversion of individual DigiMon data components

Different data types carry different information about the subsurface, so there should be advantages in combining information from different data types when seeking to infer subsurface properties such as changes in CO2 saturation and pressure with time. We have considered the following data types: conventional seismic data; gravimetric data, and; distributed acoustic sensors (DAS) data. These data types, and the corresponding forward-modelling techniques, are described in Vandeweijer et al., 2021, Bhakta et al., 2023. An important aim for the DigiMon project is to qualify a cost-efficient monitoring system for use with large-scale CO2 sequestration. It is therefore of particular interest to assess if it is possible to obtain satisfactory monitoring results without using the most acquisition-expensive data type(s). Acquisition of conventional seismic data is considerably more costly than acquisition of gravimetric and DAS data combined. In addition to comparing the monitoring performances of the individual data types, we have therefore also compared the performance of gravimetric and DAS data combined, to that of conventional seismic data. We have developed a modelling framework for geophysical monitoring with the abovementioned geophysical data types that in addition to a best estimate of the monitoring target also quantifies the uncertainty in that estimate. The framework uses an ensemble-based implementation of Bayesian (and sequential Bayesian) statistics to achieve this at an affordable computational cost for the numerical examples studied. If the correct monitoring results are known, which they will be if a study with synthetic data is conducted, we can therefore assess with what certainty a particular data type produced better results than another data type for the study example in question

Framework for forward modelling of the DigiMon data

Deliverable D2.1 adds to the main goal of WP2 of the ACT DigiMon project, which is to develop the integrated DigiMon system. The key target for WP2 is to optimally integrate various system components into a reliable and usable system. This deliverable (D2.1) describes the key forward modelling tools of the DigiMon monitoring system. In particular, the modelling tools required to simulate the data response for the individual DigiMon system components that is; Distributed Acoustic Sensing (DAS), conventional seismic, 4D gravity data, and seafloor deformation.Framework for forward modelling of the DigiMon datapublishedVersio