Acidification of Geothermal Wells Laboratory Experiments - Geothermal Reservoir Well Stimulation Program

Deep neural networks (DNNs) have the potential to streamline the integration of seismic data for reservoir characterization by providing estimates of rock properties that are directly interpretable by geologists and reservoir engineers instead of elastic attributes like most standard seismic inversion methods. However, they have yet to be applied widely in the energy industry because training DNNs requires a large amount of labeled data that is rarely available. Training set augmentation, routinely used in other scientific fields such as image recognition, can address this issue and open the door to DNNs for geophysical applications. Although this approach has been explored in the past, creating realistic synthetic well and seismic data representative of the variable geology of a reservoir remains challenging. Recently introduced theory-guided techniques can help achieve this goal. A key step in these hybrid techniques is the use of theoretical rock-physics models to derive elastic pseudologs from variations of existing petrophysical logs. Rock-physics theories are already commonly relied on to generalize and extrapolate the relationship between rock and elastic properties. Therefore, they are a useful tool to generate a large catalog of alternative pseudologs representing realistic geologic variations away from the existing well locations. While not directly driven by rock physics, neural networks trained on such synthetic catalogs extract the intrinsic rock-physics relationships and are therefore capable of directly estimating rock properties from seismic amplitudes. Neural networks trained on purely synthetic data are applied to a set of 2D poststack seismic lines to characterize a geothermal reservoir located in the Dogger Formation northeast of Paris, France. The goal of the study is to determine the extent of porous and permeable layers encountered at existing geothermal wells and ultimately guide the location and design of future geothermal wells in the area.

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Storage Capacity of Geothermal Resources in Gaoling Group over the Eastern Half of Xi’an Depression

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.512-515.894 ◽

2012 ◽

Vol 512-515 ◽

pp. 894-899

Author(s):

Yun Feng Li ◽

Bo Li ◽

Yao Guo Wu ◽

Jiang Xia Wang ◽

Zhong Hua Xu ◽

...

Keyword(s):

Geothermal Energy ◽

Storage Capacity ◽

Geothermal Reservoir ◽

Geothermal Resources ◽

Water Storage Capacity ◽

Calculation Region ◽

Geothermal Fluids ◽

Distribution Parameters ◽

Geothermal Wells ◽

Element Method

Weighted element method is proposed in this paper to improve the accuracy of calculating storage capacity of geothermal reservoirs. By making full use of all geothermal wells in the calculation region，this method had been proposed by the author in 2011,which is defined by every three neighboring geothermal wells. The calculation region is divided into many calculation elements. As a result, the entire calculation region of the distribution parameters is discretized into independent in each element with lumped parameters. The arithmetic mean of three-node parameters in each element is used as the lumped parameter, and the block with the same set of parameters is divided into calculation regions as small as possible. The effect of one element as well as its parameters in the entire.Calculation region depends on the weight of the area of this element in the whole calculation area. The weighted element method can be used to calculate the volumetric water storage capacity of geothermal fluids, elastic release storage capacity, geothermal storage capacity of volume water, geothermal energy storage capacity of elastic releasing water, geothermal storage capacity of geothermal reservoir rocks for each element, respectively. The storage capacities of various elements and the entire calculation regions can be calculated with superposition. The proposed approach was used to calculate the storage capacity of geothermal resources in Gaoling Formation of Xi’an Depression, in which data of 57 existing geothermal wells were available. If the geothermal energy recovery is set at 10% and the exploitation remains stable, the geothermal energy contained in the geothermal reservoir can be extracted for more than 7,000 years. Under the current conditions of exploitation technology, the actual geothermal energy that can be effectively exploited and used is 1915.6025×109kcal, which is equivalent to standard coal of 27.36575×104t.

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