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Brine reservoir prediction and resource evaluation method for underground brine-type potash and lithium deposits

A technology of underground brine and evaluation method, which is applied in the directions of measurement, earthwork drilling, seismic signal processing, etc. It can solve the problems that the number of groundwater samples detected cannot meet the calculation of resource amount, there is no logging response characteristic, and various underground brine-type lithium mines cannot be solved. Parameter calculation and other issues

Active Publication Date: 2022-07-05
CHENGDU UNIVERSITY OF TECHNOLOGY
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AI Technical Summary

Problems solved by technology

However, due to the insufficient number of drilling wells, it is not possible to effectively conduct underground sampling or drilling in the area; or the number of drilling wells is sufficient, but lithium ion is a trace element that can only be detected with special equipment
In both cases, the number of detected groundwater samples cannot meet the needs of resource calculation.
[0005] (2) The resource calculation of underground liquid mineral deposits usually uses geophysical data to calculate underground reservoir thickness, porosity, water saturation and other parameters. However, the formation containing lithium-rich brine has no logging response characteristics that are different from other formations , it is impossible to calculate various parameters required for underground brine-type lithium mines

Method used

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  • Brine reservoir prediction and resource evaluation method for underground brine-type potash and lithium deposits
  • Brine reservoir prediction and resource evaluation method for underground brine-type potash and lithium deposits
  • Brine reservoir prediction and resource evaluation method for underground brine-type potash and lithium deposits

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example 1

[0056] Taking the first member of the Leikoupo Formation in the Moxi area of ​​central Sichuan as an example, according to Lei Yi 1 The multi-well intersection analysis diagram of the sub-section shows that the gypsum rock has a high impedance value and is easy to distinguish from other lithologies. Dolomite and limestone are superimposed in terms of impedance and gamma, and it is difficult to distinguish them. The water content of the brine reservoir is relatively high, and the potassium-rich brine is rich in a large amount of electric ions. The formation shows low resistivity. The resistivity of the samples with porosity ≥ 2% is mostly less than 500Ω·m, and the resistivity of the brine reservoir is higher. Low, generally less than 200Ω·m. This shows that the brine reservoir has the petrophysical characteristics of low gamma, high porosity, low impedance and low resistivity, so the above characteristics can be used to identify the distribution of the brine reservoir.

[005...

example 2

[0076] Taking the first member of the Leikoupo Formation in the Moxi area of ​​central Sichuan as an example, Figure 5 Plots of positive correlation functions for potassium and lithium content are shown.

[0077] Firstly, according to the prediction method of the brine storage strata for underground brine-type potash and lithium ore, the plane distribution of the brine storage strata is predicted. The specific steps are as follows:

[0078] (1) Based on the logging data, the nonlinear relationship between wave impedance, natural gamma, porosity and resistivity is established.

[0079] (2) Based on the wave impedance of seismic inversion, the nonlinear mapping of wave impedance to natural gamma, porosity and resistivity is obtained by neural network, so as to obtain the wave impedance, natural gamma, porosity, and Physical inversion of resistivity.

[0080] (3) Using the three-dimensional multi-attribute fusion technology to describe the spatial distribution characteristics ...

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Abstract

The present invention provides a method for predicting and evaluating the resource quantity of brine reservoirs of underground brine-type potash mines and lithium mines. Based on the wave impedance of seismic inversion, obtain the physical property inversion volume of various parameters of the formation, predict the distribution of the brine storage formation with the characteristics of low gamma, high porosity, low impedance and low resistivity, and draw the parameters of the brine storage layer The resource evaluation method is to use the above method to predict the spatial distribution characteristics of underground brine, detect the potassium ion content of the underground brine sample, and use the positive correlation of potassium and lithium content to estimate the lithium ion content in the corresponding brine sample, Thus, various parameters required for the assessment of underground brine-type lithium ore resources are calculated. The invention can more accurately predict the spatial distribution of the brine layer, and realize the effective implementation of the underground brine-type lithium ore and potassium ore resources.

Description

technical field [0001] The invention relates to the technical field of a method for calculating liquid mineral resources, in particular to a method for predicting the brine storage layer and evaluating the resources of underground brine-type potash and lithium mines. Background technique [0002] Lithium mainly exists in two forms in nature as solid resources in spodumene, lepidolite and liquid resources in brine. Lithium deposits have been discovered in at least 20 countries around the world, including Chile, Bolivia, China, Australia, United States, Brazil, Portugal, Argentina, Russia, Zimbabwe, Democratic Republic of Congo, Serbia, Spain, Austria, Israel, Ireland, France, India, South Africa , Finland, Sweden, Mozambique, etc. China is rich in lithium ore resources, with many deposits and large scale. It is one of the dominant minerals in my country. The spatial distribution of lithium deposits has a regional concentration trend. The reserves are obviously concentrated i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): E21B49/00E21B47/00G01V1/40G01V1/28
CPCE21B49/00E21B47/00G01V1/40G01V1/28
Inventor 陈小二张兵杨凯裴文彬林晓杨张赛明王昌勇邢凤存郑荣才
Owner CHENGDU UNIVERSITY OF TECHNOLOGY