GNGTS 2022 - Atti del 40° Convegno Nazionale

390 GNGTS 2022 Sessione 3.1 INTEGRATED MULTI-GEOPHYSICAL AND GEOLOGICAL WORKFLOW FOR GEOTHERMAL RESOURCE EXPLORATION AND CHARACTERIZATION R. Bachrach 1 , T. Cassola 2 , L. Masnaghetti 3 , G. Sosio 4 1 Schlumberger, Denver, USA 2 Schlumberger, The Hague, Netherlands 3 Schlumberger, Milan, Italy 4 Schlumberger, Paris, France Identifying and confirming the resource is a crucial aspect for the success of a geothermal project. Reducing the uncertainties associated with the structural settings, the lithology and properties of the potential reservoirs, and the expected temperature of the geothermal fluid allow de-risking the subsequent activities, and increasing the chances of success of the first well drilled in a prospect, which is the costliest item in the project lifecycle. Geophysics-centered, data-driven solutions are the keystone of this effort, aiming at integrating the information available prior to drilling to quantify the relevant properties of the subsurface and setting the stage for further geological, fluid and heat flow, and geomechanical modeling. These solutions can be delivered in a consolidated digital platform to perform the workflow in the most consistent fashion across different disciplines. The analysis of the geothermal potential based on acquired geophysical data is the first step. Magnetotelluric and gravity data provide a cost-effective source of 3D data to delineate the structural lineaments and fault network, defining the geological framework at the basin scale or at smaller scales. Multi-physics measurements and interpretation allow to map the lateral changes in lithology, supported by rock-physics characterization of the reservoir properties. Highly automated solutions utilizing advanced litho-petro-elastic engines are used for accurate modeling of subsurface properties and temperature in 3D (Fig. 1). Thermal properties Fig. 1 - Utilization of advanced litho-petro-elastic models (left) to estimate thermal conductivity (center) and temperature distribution (right). Fig. 2 - Inverse geothermal modeling used to derive impedance, lithology and thermal conductivity.