Fines migration, particularly the movement of dislodged clays, significantly impacts formation damage and well productivity. Clays in porous media comprise authigenic particles formed during geological processes and detrital particles that have broken off, migrated to depositional sites. Extensive studies exist on detrital particles, but the theory for authigenic clay-induced formation damage is lacking. This work aims to outline the laboratory test design, procedures, and theoretical modeling for addressing this gap, focusing on Australian cores with emphasis on CO2 storage.
Two series of coreflood experiments were conducted using sandstone cores with specific characteristics, including kaolinite content and initial permeability. The first series varied flowrates progressively, while the second series conducted low-rate injections with decreasing salinity. Pressure drops across the cores and effluent particle concentrations were measured. Analytical models were used to match the data for both particle types.
The laboratory data closely align with the mathematical model for both coreflood series, revealing a 46% reduction in permeability. The type curve, indicating clay mobilization, exhibits non-monotonic concentration variations. Authigenic to detrital kaolinite ratios range from 20:1 to 1:2, with authigenic kaolinite causes octuple more damage than detrital particles at high production rates. Determining the Maximum Retention Function (MRF) for each core type enables precise formation damage calculations.
This work introduces an innovative experimental approach for assessing fines migration-induced formation damage caused by authigenic and detrital clays, along with a mathematical model. Additionally, a recently developed mathematical model facilitates the determination of coefficients through laboratory tests and predicts skin factors in production wells.

Carbon capture and storage known as CCS, which involves injecting CO2 into subsurface, is an increasingly popular process for mitigating human caused greenhouse gas emissions. In order to ensure the safety and efficacy of CCS implementation, it is must to possess a comprehensive understanding of the complex behaviour of CO2 plumes within geological formations and their potential impact on ground surface deformation. Therefore, conducting research and analysis on these critical aspects is of vital importance. This research provides a methodology to anticipate ground surface deformations, which is resulting from the motion of CO2 plumes utilizing an advanced machine learning (ML) technique. The ML surrogate model has been developed using conditional Generative Adversarial Networks (cGAN). The dataset used for the model training and testing comprises ground surface measurements (InSAR, tiltmeters, etc.), reservoir properties, as well as pressure/volume data. The model has been trained and tested using a set of samples created using a forward finite element model. Results show that the surrogate model is capable of predicting reasonably accurate results while running much faster than the forward model.

Geomechanics play an important role in any underground activity, such as CO2 and H2 geo-storage, owing to the considerable hazards linked to the injection and withdrawal of fluids into and from the subsurface. In order to quantify these risks, knowledge of full stress tensor is required. Yet, most of our stress information in the Australian target basins for geo-storage, is limited to the stress orientations, where stress magnitude data is sparse. 3D geomechanical modelling is proved to be an invaluable tool for prediction of full stress tensor. Nevertheless, a model requires some stress magnitude data in order to tune the model to be representative of real stress state. In situations where stress magnitude data is lacking, this means that the model is susceptible to significant uncertainties.
Herein, we present a novel strategy for stress modelling, which involves the utilization of indirect data such as borehole breakouts, drilling-induced fractures, seismic activity records, and formation integrity tests to calibrate 3D geomechanical model. We employ northern Bowen Basin as a case study for a comprehensive 3D geomechanical modelling approach comprising: 1) construction of 3D geological model, 2) analysis of direct and indirect stress information, and 3) building a 3D geomechanical model. We assess all the indirect information in the model’s volume to narrow down the model predictions and find the most reliable stress state. This innovative approach is an important step forward in stress modelling of Australian basins, where lack of stress magnitudes is a great challenge for geomechanical assessment of geo-storage.

Geological injection of CO2 plays a key role in contributing the CCUS technology and underpinning the Net Zero by 2050 strategy, for example, aiding the preconditioning of orebody mining through CO2-based fracturing, and reducing atmospheric emissions of greenhouse gases through sequestration within deep underground reservoirs. However, the frequent injection activities would disturb the stability of surrounding fault zone and carry the risk of inducing seismic events, posing public concern.
The fault reactivation process involves interactions among the fluid flow and the mechanical response of the rock matrix. To investigate the effects of CO2 properties, upon entering a fault, on the rupture process (shear rupture and opening rupture of a critically stressed fault), an extensive fully coupled simulation is performed using a robust finite element fracture-contact model. Fault aperture variation due to both normal and shear stress variation has been captured through the contact model. A slip-weakening friction model is employed to capture the fault shear slip. Results show that the fault’s hydraulic conductivity variation due to both aperture and CO2 properties variation, in turn has impacted the CO2 plume front in the fault.