| Title | Probalistic forecasts of well flow rate and spacing for low enthalpy geothermal projects |
|---|---|
| Authors | Schaaf, T; Egermann, P; Patriarche, D; Promis, M-P |
| Year | 2016 |
| Conference | European Geothermal Congress |
| Keywords | Uncertainty quantification, probabilistic forecasts, well spacing, Dogger formation, Basin of Paris |
| Abstract | Like in the oil and gas business or mining industry, getting reliable production forecasts is a key aspect of any geothermal project. Our application cases are low enthalpy projects, located in the Paris Basin and exploiting the Dogger formation. Typical development plan consists of a doublet (a pair of one injector and one producer wells) which long-term sustainable flow rates and thermal breakthrough timing should be thoroughly assessed. Properly analyzing and quantifying the technical and economical uncertainties allows for deciding the development of such a project. Focusing on the subsurface uncertainties, we have to quantify the ones that may impact a geothermal well productivity/injectivity. Such uncertain static parameters could include for example the net pay, the permeability, the well skin or the expected pressure and temperature at reservoir level. Using the power of geostatistics, which allow estimating and simulating the spatial variability of the properties we are interested in, together with advanced workflow capabilities of geomodelling software, we are then able to generate hundreds of equiprobable realizations for each of the properties considered and to extract key statistics for a prospect zone. These realizations are conditioned to the data gathered on existing wells in the nearby zone. Those distributions, in a probabilistic view, quantify the uncertainty on the subsurface and can be inputs for the dynamic modelling part. This dynamic modelling , for a fixed well architecture and a given surface facilities operating pressure, computes the pressure drops in the reservoir and the well. Using the nodal analysis, for the given reservoir and well properties, we estimate what might be the flow rate and associated flowing reservoir pressure. Accordingly, we estimate the extra pressure drop that is needed to achieve a target rate as well as simulate the use of a down-hole pump. Finally, for each of the target rates, a distribution of drawdowns (associated to the subsurface uncertainties) is obtained. We are then able, for a given maximum drawdown value (derived from the well architecture) to derive the probability of achieving target flow rates. This approach has also been coupled with an analytical formula to estimate the associated optimal well spacing value for several values of nominal rate and thermal breakthrough time. Using this workflow has made possible to get probabilistic forecasts of flow rate and well spacing and give properly the uncertainty assessment of any low enthalpy geothermal project capacity and performance, which are of primary importance for decision making. |