基于多源融合建模和热−流耦合模拟的张掖盆地地热资源分布特征及成因机制

尹政; 陈庆祥; 何剑波; 王春磊; 骆进

doi:10.19509/j.cnki.dzkq.tb20230590

基于多源融合建模和热−流耦合模拟的张掖盆地地热资源分布特征及成因机制

doi: 10.19509/j.cnki.dzkq.tb20230590

尹政^1,,
陈庆祥²,
何剑波¹,
王春磊¹,
骆进^2, ,

1.
甘肃省地质矿产勘查开发局水文地质工程地质勘察院，甘肃张掖 734000
2.
中国地质大学（武汉）工程学院，武汉 430074

基金项目: 甘肃省自然资源厅科技创新项目（编号202232）；甘肃省2023年度省级基础地质调查项目（编号202330）；聚光太阳能地热温室储热系统能源转换效率研究（NO.2023AED197）

详细信息

作者简介:
尹政：E-mail：zyyz8029@163.com

通讯作者:
E-mail：jinluo@cug.edu.cn

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- 文章访问数: 360
- PDF下载量: 46
- 被引次数: 0
出版历程
- 收稿日期: 2023-10-25
- 录用日期: 2023-12-12
- 修回日期: 2023-12-04
- 网络出版日期: 2023-12-18

Spatial characteristics and genetic mechanism of geothermal resources in Zhangye Basin by multi-source fusion modeling and heat-flow coupling simulation

1.
Institute of Hydrogeoloical and Engineering Geology, Gansu Provincial Bureau of Geology and Mineral Exploration and Development, Zhangye Gansu 734000, China
2.
China University of Geosciences (Wuhan), Faculty of Engineering, Wuhan 430074, China

More Information

Author Bio:
E-mail：zyyz8029@163.com

Corresponding author: E-mail：jinluo@cug.edu.cn

摘要

摘要:
传统基于已有钻孔数据插值的温压场分析方法不能很好地反映地热资源渗流−传热耦合过程，造成对地热资源的成因机制认识不足。首先基于钻孔信息、物探信息、高程数据等多源数据进行相互融合，建立了张掖盆地高精确度三维地质模型。对比传统插值模型可知，多源数据融合建模能提升孔间地层精度50～300 m。基于三维地质模型开展了盆地渗流−传热场耦合数值模拟，对比关键点空间插值法，多场耦合分析更合理地揭示研究区储层温压特征。研究区地热水头在盆地中心靠东南处较高，逐渐向盆地北东方向降低，呈现整体由南东向北西渗流，经断层补给储层，渗流过程中被地温场充分地加热，随后由于储存埋深变浅和盖层变薄失去热量，温度场表现为中间高四周低，中心温度可达78℃。最后，建立了三维地热概念模型，结合构造、水文地质和地热地质条件等综合解释了盆地地热资源的成因机制。较之以往的二维模型，本研究三维概念模型和热−流耦合的方法更准确地描述了资源地空间分布特征和更合理地解释了资源成因机制。研究结果揭示了储层地下水由南东向北西渗流过程及盆地地热资源菱形叶状分布的成因机制，为精确圈定地热靶区和资源合理开发利用提供理论依据。
- 张掖盆地 /
- 三维地质模型 /
- 地热资源 /
- 温压特征 /
- 成因机制
Abstract:
The traditional temperature and pressure field analysis approach is based on the interpolation of existing borehole data, which cannot accurately represent the seepage-heat transfer coupling process of geothermal resources, resulting in insufficient understanding of the genetic mechanism of geothermal resources. To overcome the drawbacks of the conventional approach, this paper built a three-dimensional geological model of Zhangye Basin by combining multi-source data including borehole information, geophysical information and elevation data. Compared with the traditional model, multi-source data fusion modeling can improve the accuracy of inter-hole strata by 50-300 m. The numerical simulation of basin seepage-heat transfer field coupling process shows that the multi-field coupling analysis describing the temperature and pressure field more reasonable than that of key-point-spatial-interpolation approach. The analysis shows the higher water head in the southeast of the basin and relatively lower heat in the northeast. this leads to the geothermal water flows from southeast to northwest and was heated up during the seepage process, and the heat was lost later when the burying depth of the reservoir becomes shallower and the cap becomes thinner. As a result, the higher temperature was determined in the basin center which can reach up to 78℃ and the lower temperature was observed in the areas surrounding with the center. Finally, a 3D geothermal conceptual model is developed to better understand the genetic mechanism of geothermal resources in terms of structural, hydrogeological, and geothermal geological perspectives. This 3D conceptual mode coupling with heat-flow transfer modeling more specifically explains the spatial distribution and reveal more clearly the underlying mechanism of forming the geothermal resources compared with conventional 2D model.The study showed the groundwater in the reservoir flows from south-east toward north-west and revealed also the formation of the rhombic-lobe shaped distribution of geothermal resources in the basin, which provides theoretical basis for the precise localization of high potential geothermal zones and for the sustainable development of geothermal resources.
- Zhangye Basin /
- 3D geological model /
- Geothermal resources /
- Temperature and pressure characteristics /
- Genetic mechanism

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图 1 研究区地理位置

Figure 1. Geographical location of the study area

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图 2 张掖盆地地热钻井分布

Figure 2. Spatial distribution of the geothermal wells in Zhangye Basin

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图 3 基于多源数据建模数据处理流程图

Figure 3. A flow chart shows the data processing of multi-source data modeling approach

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图 4 研究区数值模型示意图

Figure 4. Numerical model of the study area

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图 5 基于单因素三维地质模型

Figure 5. Geological model built based on a single factor and the deviation

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图 6 基于多源数据三维地质模型

Figure 6. Three-dimensional geological model built by multi-source fusing method

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图 7 研究区新近系白杨河组水位高程分布对比图

Figure 7. Comparison of the water level distribution of Neogene Baiyanghe Formation using interpolating method with numerical modeling

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图 8 研究区新近系白杨河组温度分布对比图

Figure 8. Comparison of the temperature distribution of Neogene Baiyanghe Formation using interpolating method with numerical modeling

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图 9 勘探井测温曲线图

Figure 9. Temperature measurements of some geothermal wells located in the study area

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图 10 研究区地热概念模型

Figure 10. A 3D geothermal conceptual model of the study area

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表 1 ZYDR1抽水实验成果

Table 1. ZYDR1 pumping test results

降次	1	2	3
静水高度/m	5.77	5.77	5.77
动水位埋深/m	130.66	84.68	48.37
水位降深/m	136.43	90.45	54.14
出水量/(m³·d⁻¹)	2640.00	1728.00	1032.00
单位出水量/(L·s⁻¹·m⁻¹)	0.22	0.22	0.22
井口出水温度/(℃)	56	55	55
抽水延续时间/h	56.5	18.25	8.75
稳定时间/h	48	16	8

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表 2 水力学参数确定

Table 2. The determined hydraulic parameters of aquifers

储层钻孔编号	第四系		新近系			白垩系
储层钻孔编号	HQ3	HQ4	LZDR1	ZYDR1	ZYDR3	ZYDR2
渗透系数K/(m·d⁻¹)	28.80	26.13	0.35	0.48	0.35	0.097
导水系数C/(m²·d⁻¹)	1696.90	1370.26	49.18	257.28	65.39	16.77

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表 3 岩土物理参数及热物性参数测试结果

Table 3. Physical parameters and thermal parameters of the collected samples

储层	颗粒密度/ (g·cm⁻³)	孔隙率/ %	导热系数/ (W·m⁻¹·K⁻¹)	比热容/ (kJ·kg⁻¹·K⁻¹)	热扩散系数/ (mm²·s⁻¹)
第四系	2.60	40	1.610	0.878	0.705
新近系(砂岩)	2.67	27.3	1.264	0.311	1.860
新近系(泥岩)	2.63	10.6	1.460	0.260	3.400
白垩系(砂岩)	2.02	25.4	1.593	0.962	0.91
白垩系(泥岩)	2.56	5.6	1.104	0.345	1.510

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表 4 地质钻孔信息

Table 4. Geological drilling information

井号	经度/（°）	纬度/（°）	井深/m	地面高程/m	祁连山山前断裂/m	龙首山山前断裂/m	第四系底/m	新近系底/m	白垩系底/m
ZYDR1	100.4211	38.94694	2601.22	1487	21.7	17.6	834	−318	−2093
ZYDR2	100.1253	38.98694	2053.08	1644	1.7	29.8	1045	13	−1112
ZYDR3	100.4842	38.79778	2714.03	1536	23.3	28.4	949	−484	−4279
MLDR1	100.6383	38.66139	2269.18	1778	23.2	34.1	1127	−417	−1384
MLDR2	100.682	38.75419	1567.02	1646	34.3	23.7	1030	−674	−1283
MLDR3	100.7289	38.64698	2350.79	1827	26.1	32.5	1064	−667	−1148
LZDR1	100.1697	39.12476	1500.59	1463	14.9	16.6	1023	432	−1760
LZDR2	100.1119	39.04029	1701.75	1587	4.2	25.9	767	261	−1280

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