Numerical Simulation And Regression Prediction For Geothermal Wells Development

With scarcity of conventional resources becoming more and more serious, the usage ofclean, green and renewable energy becomes the focus of next energy construction adjustment,which obtains attention all over the world. Among those new energy resources, the geothermalresource become a real priority because of its high reserves, convenient utilization and strongsustainability. Geothermal exploitation means of oil wells at present are water injection andCO2plume system. The latter, as a new method, get the attention of industry because of itsability of strong heat getting and potential advantage for CO2sequestration. But no matter whatkind of heating method, thermal effect and cause of some reservoir parameters and injectionconditions, and regression prediction with intelligent algorithm for thermal effect, has not beenreported.The thesis was written as follows: firstly, modeling for geothermal development of oilwells with injecting water and supercritical carbon dioxide with numerical simulation method;by changing the corresponding reservoir parameters and injection conditions, we computed itsinfluences on geothermal development of oil wells and analyzed its causes according to timepoint, degree and style of influences; secondly, according to the simulation result, we find outthe corresponding influencing factors of different fluid for geothermal development of oil wells;and then using deep learning as the method to predict thermal efficiency of multi-wells model,single well model and change trend of thermal efficiency. Through the experiment of numericalsimulation and intelligent regression, the following conclusions were reached：1. Through numerical Simulation of water and supercritical carbon dioxide injectiongeothermal exploitation system, we can see that the latter has superior buoyant, thoughenthalpy is lower than the water, its overall thermal efficiency nearly doubled to water.2. Improvement of parameters like reservoir temperature, injection volume, injectionrate, specific heat capacity of reservoir rock, diameter of injection well and production well,fluid injection temperature will increase thermal efficiency of water injection; Improvementof initial salt concentration of reservoir will reduce thermal efficiency of water injection; pressure, permeability and thermal conductivity of reservoir rock has little effect onthermal efficiency of water injection.3. Improvement of parameters like reservoir temperature, permeability of reservoirrock, injection volume, injection rate, thermal conductivity of reservoir rock, specific heatcapacity of reservoir rock, initial temperature of injected fluid can increase thermalefficiency of scCO2injection. Supercritical carbon dioxide injection geothermalexploitation system is very sensitive to the change of reservoir pressure, which will lead itto change a lot. Increasing initial level of reservoir salinity will reduce thermal efficiency ofscCO2injection in two-phase flow of water and CO2. Affection of diameter of injection andproduction well on thermal efficiency of scCO2injection should be depended on reservoirpressure.4. Deep belief network can complete the high dimensional feature extraction. Throughthe comparison between it and traditional artificial neural network, it was found that DBNshad been effective enough in regression prediction for multi-wells model, single-wellmodel and change trend of thermal efficiency, and could find rules from abstractcharacteristics of sample data, then predict thermal effect. The result proved thatforecasting data fitted well with the original data, but the side effect is time-consuming ifthe amount of hidden layer nodes was too big. All in all, intelligent prediction forgeothermal development of oil wells with injecting water and scCO2is more flexible, andable to build an adaptive network model, which is suitable for changes of initial injectionconditions and reservoir conditions at any time. Compared with the traditional numericalsimulation software, this method has certain advantages in some aspects, and has valuablereference for the future production.