Thermal Effect on Formation Stability Due to Heterogeneity

This study evaluates physical and chemical changes induced by high thermal gradients on the formation and their impact to the stability. The heat sources that effect the formation’s stability are varied, including drilling (due to drilling bit friction), perforation, electromagnetic heating (laser or microwave), and thermal recovery or stimulation (steam, resistive heating, combustion, microwave, etc.). This study uses an integrated approach to characterize rock heterogeneity and mapping heat propagation from different heat sources. The information obtained from the study is vital to accurately design and enhance well completion and stimulation This is an integrated analysis approach combining different advanced characterization and visualization techniques to map heat propagation in the formation. Advanced statistical analysis is also used to determine the key parameters and build fundamental prediction algorithms. Characterization on the samples was performed before, during, and after the exposure to thermal sources; it comprised thin-section, high speed infrared thermography (IR), differential thermal analysis and thermogravimetric analyzer (DTA/TGA), scanning electron microscope (SEM), X-ray diffraction (XRD), X-ray fluorescence (XRF), uniaxial stress, and autoscan (provide hardness, composition, velocity, and spectral absorption). The results are integrated, and machine learning is used to derive a predictive algorithm of heat propagation and mapping in the formation with reference to the key formation variables and heterogeneity distribution. Rock heterogeneity affects the rate and patterns of heat propagation into the formation. Within the rock sample, minerals, laminations, and cementations lead to a heterogeneous, and sometimes anisotropic, distribution of thermal properties (thermal conductivity, heat capacity, diffusivity, etc.). These properties are also affected by the rock structure (porosity, micro-cracks, and fractures) and saturation distribution. The results showed the impact of heat on the mechanical properties of the rocks are due to clays dehydration, mineral dissociations, and micro cracks. High speed thermal imaging provides a unique visualization of heat propagation in heterogeneous rocks. Statistical analysis identified key parameters and their impact on thermal propagation; the output was used to build a machine learning algorithm to predict heat distributions in core samples and near-wellbore. Characterizing rock properties and understanding how heterogeneity modifies heat propagation in rocks enables the design of optimal completion and stimulation strategies. This paper discusses how advanced characterization and analysis, combined with novel algorithms, can improve this understanding, and unleash innovation and optimization. The data and information gathered are critical to develop numerical models for field-scale applications.