Effect of stress-dependent microannulus aperture on well leakage

Debonding at the cement-casing interface is recognized as a principal failure mechanism leading to CO_(2) leakage in wells.This detachment gives rise to a microannulus,which notably possesses greater permeability than undamaged cement,undermining its sealing efficacy.Conventionally,the permeability of the microannulus is regarded as a uniform value throughout the well.However,fundamentally,a microannulus is one type of fracture,and its gap or aperture size is affected by the effective stress.In this work,we developed a unique experimental apparatus.This equipment facilitates the curing of cement inside a steel casing,the formation of a microannulus between the casing and the cement,and the investigation of the fluid flow dynamics along the microannulus under laboratory-replicated in situ conditions.The microannulus was formed by injecting fluid from one end of the setup,and receiving similar amount of fluid on the other end signified the development of the leakage channel.Additionally,strain gauges affixed to the casing’s external surface yielded key information on the microannulus’s opening and closure.We observed a noticeable decline in microannulus hydraulic aperture(or permeability)in relation to effective stress and an exponential equation fits their relationship.Our findings also indicate a distinct behavior when comparing liquid CO_(2) with water.Specifically,it is easier for liquid CO_(2) to create the microannulus.However,the hydraulic aperture range for this microannulus(0.7-6 mm)is considerably smaller than that created by water flow(2-17 mm).Finally,we integrated the stressdependent microannulus aperture size into the combined analysis of well mechanical integrity and well leakage.The outcomes consistently demonstrated that when factoring in the stress-dependent aperture sizes,the leakage rates are 3e5 times compared to a fixed aperture model.The traditional assumption of a constant aperture significantly underestimates fluid leakage risks.

Machine Learning and Data Fusion Approach for Elastic Rock Properties Estimation and Fracturability Evaluation

Accurate rock elastic property determination is vital for effective hydraulic fracturing,particularly Young’s modulus due to its link to rock brittleness.This study integrates interdisciplinary data for better predictions of elastic modulus,combining data mining,experiments,and calibrated synthetics.We used the microstructural insights extracted from rock images for geomechanical facies analysis.Additionally,the petrophysical data and well logs were correlated with shear wave velocity(Vs)and Young’s modulus.We developed a machine-learning workflow to predict Young’s modulus and assess rock fracturability,considering mineral composition,geomechanics,and microstructure.Our findings indicate that artificial neural networks effectively predict Young’s modulus,while K-Means clustering and hierarchical support vector machines excel in identifying rock and geomechanical facies.Utilizing Microscale thin section analysis in conjunction with fracture modeling enhances our understanding of fracture geometries and facilitates fracturability assessment.Notably,fracturability is controlled by specific geomechanical facies during initiation and propagation and influenced by continuity of geomechanical facies in small depth intervals.In conclusion,this study demonstrates data mining and machine learning potential for predicting rock properties and assessing fracturability,aiding hydraulic fracturing design optimization through diverse data and advanced methods.

Shale characteristics impact on Nuclear Magnetic Resonance (NMR) fluid typing methods and correlations

The development of shale reservoirs has brought a paradigm shift in the worldwide energy equation.This entails developing robust techniques to properly evaluate and unlock the potential of those reservoirs.The application of Nuclear Magnetic Resonance techniques in fluid typing and properties estimation is well-developed in conventional reservoirs.However,Shale reservoirs characteristics like pore size,organic matter,clay content,wettability,adsorption,and mineralogy would limit the applicability of the used interpretation methods and correlation.Some of these limitations include the inapplicability of the controlling equations that were derived assuming fast relaxation regime,the overlap of different fluids peaks and the lack of robust correlation to estimate fluid properties in shale.This study presents a state-of-the-art review of the main contributions presented on fluid typing methods and correlations in both experimental and theoretical side.The study involves Dual Tw,Dual Te,and doping agent's application,T1-T2,D-T2 and T2sec vs.T1/T2 methods.In addition,fluid properties estimation such as density,viscosity and the gas-oil ratio is discussed.This study investigates the applicability of these methods along with a study of the current fluid properties correlations and their limitations.Moreover,it recommends the appropriate method and correlation which are capable of tackling shale heterogeneity.