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Novel applications of gravity gradiometry for the detection and monitoring of sequestered CO2

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posted on 2022-03-28, 21:20 authored by Samuel John Matthews
Carbon Capture and Storage (CCS) is a technique for the reduction of greenhouse gases in the atmosphere, involving the drawdown of atmospheric or emitted CO2, and its sequestration into geological reservoirs. Its effectiveness depends on the immobility of the sequestered fluid, and CCS projects depend critically on remote monitoring to ensure that the sequestered material does not escape into the atmosphere. The monitoring of CCS sites is largely dominated by seismic methods, alongside supplementary techniques such as gravity, electromagnetics, and geochemical monitoring. Hitherto, gravity gradiometry has not been utilised extensively for the monitoring of CCS sites, as an extensive modelling framework and sensitivity analysis, to discern its viability for monitoring CO2 sequestration, has been lacking. The aims of this project are to assess and develop modelling framework for downhole gravity gradiometry, and a method to assess uncertainties in modelled results, and thus the sensitivity of the technique, using a Monte Carlo approach. The approach is applied to a number of existing CCS projects, including the CO2CRC's Otway CCS demonstrator project, to assess the potential of gravity and gravity gradiometry to monitor sequestered reservoir fluids, in both downhole environments, and remotely. The initial phase of this work involved constructing a simple benchmark numerical model of a reservoir density anomaly, and developing a Monte Carlo simulation approach to assess how the density and spatial uncertainties in a geological model relate to the final uncertainties in the modelled response; and ultimately the sensitivity of gravity gradiometry when applied in a downhole setting for the detection of sequestered CO2. In the initial benchmark, the reservoir was modelled as a simple prism, with a density contrast constrained by the Otway project petrophysical logs. Three boreholes were then modelled at varying distances from the centre of mass of the prism. Strong downhole gravity gradient signals were observed surrounding the reservoir prism, with some components of the gradient tensor demonstrating high sensitivity, notably the vertical gradient Gzz which displays a mean signal up to ~80 Eötvös within the centre of the prism, with a standard deviation (SD) of ±~20 Eötvös. The horizontal components were strongly perturbed peripheral to the prism mass anomaly, with the Gxx component adjacent to the prism displaying a signal of ~-40 Eötvös (SD of ±~10 Eötvös). The uncertainty and sensitivity analysis was then expanded to a reservoir scale regional geological model, and tested with data from flow simulations of the Otway Project CCS site. Results seen here again displayed a strong ability to detect various features within the reservoir - such as raw geology; net density change; and timelapse fluid migration. When modelling the regional geology prior to fluid injection, the downhole gravity gradiometry demonstrates the ability to delineate the relative geology of the region, and is particularly sensitive to subsurface layering. To explore the technique's capacity to monitor subsurface fluids, models of the time-variable net density change caused by the sequestration of CO2 were developed, and showed that downhole gravity gradiometry performed on a heterogeneous reservoir was capable of identifying the sequestered plume. Characterisation of the noise implicit in these reservoir models identified two independent sources, the geological noise - arising from the laterally complex and heterogeneous geology of the reservoir, and the noise associated with the time-variable fluid flow. Whilst the geological variations in density have characteristically large uncertainty distributions (input standard deviations of >±100 kg/m3), they are coherent throughout a reservoir injection, and time-series measurements of potential field components are only sensitive to variations and uncertainties in reservoir fluid density, which exhibit much lower standard deviations (~±25 kg/m3). In the latter cases, for Monte Carlo time-series models fluid injection, the output standard deviation for many components, notably Gz, Gzz, Gxx, was generally larger than the output uncertainties. Anomalies as high as ~50 Eötvös were observed for the Gzz component of the gradient tensor (SD ~±20 Eötvös), and as high as ~30 Eötvös for the Gxx component (SD ~±10 Eötvös), suggesting for the Otway geological system, downhole gravity gradiometry is capable of detecting the sequestered CO2 plume over the system noise associated with the injection. In addition, a model containing a simulated fluid leak above the reservoir was performed. Downhole gradiometry demonstrated the ability to discern a small leak with mass of ~16,000 tonnes (representing ~1/4 of the total injecta), with local signal as high as ~70 Eötvös for Gzz - above the detection threshold for current generation downhole gradiometers. Lastly, the reservoir modelling approach was expanded to remotely acquired satellite gravity data acquired from the GRACE (Gravity Recovery and Climate Experiment), and gravity gradiometry from GOCE (Gravity Field and Steady State Ocean Circulation Explorer) missions. The case studies modelled here were three CCS sites of varying scale (Sleipner, North Sea; In Salah, Algeria; and Otway, Australia) in addition to a large scale oil extraction site (Ghawar Oilfield, Saudi Arabia). All these reservoirs were experiencing mass change to injection (CCS) or petroleum extraction (Ghawar) over the time period the satellite missions were active. Geoid and gravity gradient data were extracted within the regional bounds of these reservoirs from satellite-derived global grids over monthly intervals, and these time-series were modelled using simple reservoir geometries. Over the period of time during which these data were acquired, the signals observed by the GRACE models displayed a strong ability to detect changes in geoid. Magnitudes of up to 1 mm were observed for the larger reservoirs, and ~0.25 mm for the smaller reservoirs, which are explainable by constrained fluid mass change within their subsurface. The gravity gradient approach was not able to conclusively replicate this success, largely due to the shorter time period during which GOCE was active and the resulting lack of data points. It was seen that the terrains overlying the reservoirs being monitored played an important role in the results; with those on land (Ghawar, In Salah, Otway) displaying signal above the level of noise (signal to noise ratio (SNR) of up to 0.49 for Ghawar) whereas the extensive noise for the marine case study (Sleipner) was larger than the reservoir signal (SNR of 0.09). The process of CCS injection involves significant mass change and density variations within the CCS reservoir. Such changes are amenable to monitoring with conventional - and unconventional - potential field techniques. Here I have demonstrated that downhole gravity gradiometry is capable of detecting subsurface fluid flow associated with CCS injection - and that the reservoir mass changes may induce observable potential field signal even satellite heights, which has important implications for global monitoring programs of the subsurface dynamics of reservoirs.


Table of Contents

Chapter One. Introduction -- Chapter Two. Background -- Chapter Three. Simplistic downhole benchmark -- Chapter Four. Regional geological simulation -- Chapter Five. Satellite reservoir monitoring -- Chapter Six. Discussion -- Chapter Seven Conclusion -- References -- Appendices.


Bibliography: pages 246-275 Empirical thesis.

Awarding Institution

Macquarie University

Degree Type

Thesis PhD


PhD, Macquarie University, Faculty of Science and Engineering, Department of Earth and Planetary Sciences

Department, Centre or School

Department of Earth and Planetary Sciences

Year of Award


Principal Supervisor

Craig O'Neill

Additional Supervisor 1

Mark Andrew Lackie


Copyright Samuel John Matthews 2018. Copyright disclaimer:




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