China Petroleum Logging Co., Ltd.
College of Geology and Environment, Xi’an University of Science and Technology

柴达木盆地西部中央凹陷区中深层卤水钾含量高,但岩性复杂,孔隙类型多样,为寻找富钾卤水层,进行钾元素测井响应规律研究,利用地层水电阻率谱与体积模型对卤水层钾离子含量进行定量评价。结果表明:基于微电阻率成像数据得到的地层水电阻率谱,通过提取均值和几何均值可有效识别水层,水层的地层水电阻率谱分布窄,谱峰靠前,平均值和几何均值较小;利用钾元素计算体积模型得到储层孔隙度、骨架及泥质含量,结合洗盐前后的电感耦合等离子体发射光谱仪(ICP-OES)可以定量评价卤水层钾离子含量;ICP-OES与自然伽马能谱测井可以对卤水层总钾含量进行标定,结合多元线性回归能够建立卤水层元素评价方法。用体积模型计算的卤水钾含量与试验结果一致性较好。研究结果能够快速、有效的判别卤水钾含量,提高卤水储层的识别能力,为预测研究区卤水空间展布提供重要依据。

The central depression area in the western part of the Qaidam Basin is rich in potassium- bearing deep brines with high development value. The deep brines have complex lithology and diverse pore types, which makes it difficult to evaluate the potassium element in the brines. In order to explore industrial grade potassium rich brine layers and study the response law of potassium element logging, quantitative evaluation of potassium ion content in brine layers was carried out using formation water re- sistance spectra and volume models. The results show that: the formation water resistivity spectrum ob- tained based on the micro-resistivity imaging data can effectively identify the water layer by extracting the mean and geometric mean, and the formation water resistivity spectrum of the water layer has a nar- row distribution, with the peak of the spectrum at the front, and the mean and geometric mean are smal- ler; the porosity, skeleton and mud content of the reservoir is obtained by using the calculated volumet- ric model of elemental potassium, and the results can be quantitatively evaluated by using the Induc- tively Coupled Plasma Emission Spectrometry spectroscopy( ICP-OES) before and after the salt wash- ing, which can be used to quantify the brine content. OES can quantitatively evaluate the potassium ion content of the brine layer; ICP-OES and natural gamma energy spectrometry logging can calibrate the total potassium content of the brine layer, and the combination of multivariate linear regression can es- tablish an elemental evaluation method for the brine layer. The lithium content of brine calculated by volumetric model is in good agreement with the experimental results, and this study can quickly and ef- fectively identify the potassium content of brine, improve the identification ability of brine reservoir, and provide an important basis for the prediction of the spatial distribution of brine in the study area.

国家自然科学基金项目(42304143);陕西省自然科学基础研究计划项目(2020JQ-747)第一作者:罗少成,男,湖北监利人,高级工程师,E-mail:luosc_cpl@cnpc.com.cn

罗少成,张程恩,程亮,等.柴达木盆地中深层富钾卤水测井识别模型[J].西安科技大学学报,2024,44(2):311-318.

LUO Shaocheng, ZHANG Cheng’ en, CHENG Liang, et al. Recognition model of potassium-rich brines in the middle and deep layersof the Qaidam Basin[ J] . Journal of Xi’an University of Science and Technology, 2024, 44( 2) : 311-318.