De-Risking Stress Testing Operations and Maximizing Injection Longevity

A calibrated geomechanical model is one of the key inputs that defines the longevity of carbon capture and sequestration (CCS) projects, ensuring cap rock integrity and maximum reservoir injectivity. The characterization of horizontal stress magnitude is pivotal for model accuracy. Stress testing is the only direct measure of stress magnitudes to calibrate the geomechanical model. The success of stress testing depends on a good understanding of the geomechanical environment and the appropriate choice of equipment. In this paper, we introduce a planning workflow that de-risks the stress testing operations and enables real-time updates of the stress profile. At the end of the stress testing program, the calibrated mechanical earth model (MEM) is then ready to be used as input for defining the injection plan. 1 INTRODUCTION In the early stage of carbon capture and sequestration (CCS) site characterization, three pillars define if a project has a chance to succeed: • Capacity–How much CO2 can be stored? • Injectivity–How fast can CO2 be injected? • Containment–What is the risk of leakage? Measuring the minimum horizontal stress magnitude in the caprock and the zone of injection will help to address injectivity and containment. With stricter government regulations for CCS projects, the measurement of the minimum stress becomes increasingly critical. This is also the case for oil & gas field development to enhance hydrocarbon recovery. The first step in a wireline formation tester stress testing workflow is to determine the feasibility of achieving formation breakdown in a target well for a defined set of downhole equipment. The chance of success (CoS) for formation breakdown along the entire interval will be computed. CoS is defined as the probability of breakdown for a given formation tester and packer specifications at the maximum differential pressure permissible for this equipment. At this stage, accurate model inputs are often not available, and parameter ranges over the full wellbore section can be used as inputs. Parameter uncertainty over the wellbore section is addressed using a probability density function (PDF). Based on the computed CoS for various packer configurations, the hardware will be selected.