Stress and fracture prediction using geomechanical reservoir models - A case study from the Lower Magdalena Valley Basin, Colombia (2019)

Proper characterisation of the mechanical and stress state of a hydrocarbon or geothermal reservoirs is crucial for optimal exploration and exploitation. The increasing complexity of discoveries push the boundaries of conventional methodologies, which often rely on local laboratory measurements or well-derived properties that may not represent the actual spatial distribution of relevant characteristics of the area. The early and accurate knowledge of pore pressure, mechanical properties and in-situ stress represent critical information to promote reservoir exploration, well placement and enhanced recovery techniques as well as avoidance of risky locations. Numerical modelling approaches serve as the solving tool as they can honour the heterogeneous and geometrical complexity of reservoir and associated structures. This study evaluates the potential and pertinence of geomechanical modelling techniques for stress and fracture prediction. The methodologies performed in this research are applied to a tight sand gas reservoir located in the Lower Magdalena Valley Basin in northern Colombia. The target reservoir is an Oligocene to Miocene sequence known as Porquero formation which is composed of low-permeability sandstones and shale layers. The area has been explored for more than 30 years but, due to its difficulty to be adequately characterised, has only become of economic interest in the last decade, thanks to the implementation of seismic methodologies and advanced petrophysical studies. The exploitation of the Porquero formation will require non-vertical drilling paths and hydraulic fracturing for economic production. Therefore, an accurate understanding of reservoir mechanics and stresses is of critical importance. In this study, different methodologies are proposed to study the general geomechanical behaviour of the stratigraphic column covered in the study area, as well as the inference of the natural fracturing behaviour along the reservoirs conforming the Porquero formation. Each methodology was developed around the data available, highlighting the integration between basin and petroleum systems modelling technique and geomechanical analysis as a pivotal approach to determine the mechanical state of a reservoir. The first modelling phase presents the performance of a complete geomechanical assessment using log-derived properties. This section includes the analysis of log and core data, as well as hydraulic fracturing tests leading to detailed 1D mechanical earth models (MEM) for each of the wells available in the study area. Subsequently, a 3D mechanical earth model was set up using two different property population methods that were tested and compared in terms of stresses. One method used a geostatistical approach based on well data mechanical models for property inter-/extrapolation, whereas the other, additionally used seismic inversion techniques to account for the vertical and lateral differences in mechanical rock properties. The combination of these methodologies serves as a base model of the present-day stress state of the area and is set to be the reference for potential predictive simulations. The second modelling phase introduces basin and petroleum systems modelling (BPSM) technology for geomechanical purposes. The method takes advantage of a robust model construction intended to assess hydrocarbon generation, migration and accumulation. It ensures that the temporal basin evolution and spatial properties variations are consistent and assumed under adequate reasoning. Pore pressure model was derived from porosity-dependent compaction laws that answer to subsidence and sedimentary registers of the basin. In-situ stresses were estimated through a poro-elastic approach. The definition of process-based mechanical properties, physics-driven pore pressure models and therefore enhanced resulting in-situ stresses, is presented as an alternative methodology to conventional modelling approaches, to perform a pre-drilling geomechanical assessment. The modelling results provide a spatial mechanical characterisation, pore pressure models and the complete stress tensor, not only for the reservoir but for each point in the model domain. The simulation shows that the ruling stress regime in the study area is a normal faulting regime with a governing orientation of SHmax in a WNW-ESE direction. At reservoir depth, vertical stress gradient (Sv) has a mean value of 23.29 MPa/km, and SHmax is on average 1.2*Shmin. The final stage of the modelling work includes the study of the potential of the developed geomechanical models to infer natural fracture networks. Such fracture models are crucial in enhancing field development and promoting efficient well placement to maximise hydrocarbon production. Two methods were tested. The first method corresponds to a stochastic simulation enhanced by the definition of geomechanical constraints and well-log derived fracture metrics. Paleo-stress selection is performed through a stress-inversion approach. The second model showcases the potential of forward modelling of BPSM-derived properties. The critical difference, in this case, is that the dynamic setup allows the step-wise definition of maximum stress orientation correspondent to defined geological stages. The overall analysis is made in terms of fracture orientation metrics (Dip angle and dip azimuth), fracture intensity and the potential of the models to reproduce observed data. The stochastically generated fracture network is based in a boundary element method, which is beneficial because of the computational speed. However, a concept of this method is the definition of homogeneous mechanical properties which may lead to oversimplified results when dealing with complex lithological distributions. On the other hand, the forward model approach, using the BPSM technology, displays great pertinence in gathering most of the evolutionary traits in the area. Moreover, the recognition of heterogeneous lithological distribution represents an enhancement and consequently leads to more reliable results. As a disadvantage, the construction endeavor of such models is of high complexity, as well as demanding in the necessity of the integration and cooperation of several disciplines to achieve a consistent result. Considering the mentioned generalities, the stochastic approach is advised for low-deformation regions, while the forward model approach may display its maximum capacity in areas with strong deformation. The significant contributions of this research are fully customized geomechanical reservoir models that can reproduce the reported mechanical behavior of the area but, moreover, are able to provide critical insights in the inter-well and undrilled regions of the model domain. The models are populated with actual field and laboratory data and are set to be the fundamental scenarios in any predictive simulation. The methods presented in this work are replicable and deployable in any other geographical and tectonic setting.