Seismic Imaging of Convective Geothermal Flow Systems to Increase Well Productivity

Abstract

A core feature of convective geothermal resource production is wellbore energy flow Q ~ ρC x T x V. E.g., for wellbore fluid of volume heat capacity ρC ~ 4.3MJ/m 3 • o C, temperature T ~ 230 o C, and volumetric flow V ~ 50L/s, wellbore heat energy production is Q~ 50MWth ~ 5MWe. Wellbore fluid flow V =2πr0φv0ℓ for open wellbore length ℓ is given in turn by the spatially variable product crustal porosity times crustal fluid velocity v ≡ φv0 at the wellbore radius r0. For a geothermal wellbore to be productive (nominal Q ~ 5MWe), locally variable bulk inflow rates v = φv0 across crustal volumes of dimension ℓ must be adequate to sustain high wellbore flows (nominal V ~ 50L/s). Wide-ranging crustal well productivity statistics show that few crustal wells flow at these rates. This is not surprising as local bulk flow ~ 10-2 m/s needed for production wellbores is decades greater than ambient bulk fluid flow ~ 10-8-10-7 m/s characteristic of natural convective geothermal systems. Such rare high flow locales must be found. While existing crustal surveys generally fix resource temperatures T with

Crustal Reservoir Flow Simulation for Long-Range Spatially-Correlated Random Poroperm Media

“…While Figures 1-10 are based on flow model computations for 2D sections embodying the spatial correlation properties of crustal flow systems, applying these spatial-correlation outcomes to actual reservoirs requires 3D computation. Via the essential universality of ambient crustal fluid flow empirics (i)-(vi), we can expand from 2D generic reservoir section flow simulations of Figs 1-10 intended for geothermal flow systems to 3D applications using recent field-scale fluid flow data acquired in crystalline basement rock [14] and hydrocarbon-bearing shale formations [7].…”

“…The 3D finite-element flow modelling procedure provided good model matches for multiple wellbore temperature profiles, indicating that 3D fluid flow modelling in spatially complex media is feasible. In a second 3D field-scale flow image, Figure 12 displays surface seismic emission acquisition/processing image data obtained during shale formation stimulation and production of a 1km-scale crustal volume [7]. The three-panel time sequence of flow stimulation of the shale formation shows tracking of seismic emission energy associated with fluid flow (white/black smudges).…”

“…What we do not, however, at present know is how to proactively deal with the entrenched and inherent statistical uncertainty caused by flow channelling arising from universal spatially correlated poroperm randomness at all scales. As drilling outcome predictions based on the law of averages are poor in spatially correlated poroperm media, we can directly see from Figure 4 and Figure 5 channelised flow the need to acquire and quantify information about the large-scale reservoir flow structure if we are to reduce the overall cost of production well drilling in convective geothermal reservoirs [7].…”

“…These numerical procedures allow flow modelling to accurately connect geothermal production wellbore interval inflow velocity v0 at wellbore sites (x0,y0,z0) to long-range spatially erratic poroconnectivity permeability structures exemplified by the empirical expression k(x,y,z) ~ exp(αφ(x,y,z)). Accurate wellbore inflow modelling of complex convective geothermal flow systems can interact efficiently with large-scale flow imaging data acquired by surface seismic sensor arrays to guide production well drilling [7]. The driver for accurate wellbore geothermal system flow modelling lies in the lognormal distribution of well productivity throughout the ambient crust [6].…”

“…The driver for accurate wellbore geothermal system flow modelling lies in the lognormal distribution of well productivity throughout the ambient crust [6]. It is proving uneconomic for convective geothermal energy production to drill large numbers of unproductive wells before locating productive and sustainable flow structures for targeted drilling [7]. Using advancing observational surface seismic sensor array data processing to remotely identify productive crustal flow systems will significantly reduce both exploration and exploitation drilling costs.…”