南海深水超浅层含水合物气层测井识别与饱和度估算方法

汤翟; 裴健翔; 赵军; 骆玉虎; 郭璃; 贾将

doi:10.19509/j.cnki.dzkq.tb20240082

南海深水超浅层含水合物气层测井识别与饱和度估算方法

doi: 10.19509/j.cnki.dzkq.tb20240082

汤翟^{1, 2,},
裴健翔^{1, 2},
赵军^3, ,,
骆玉虎^{1, 2},
郭璃^{1, 2},
贾将³

1 .
中海油海南能源有限公司，海口 570312
2 .
中海石油（中国）有限公司海南分公司，海口 570312
3 .
西南石油大学地球科学与技术学院，成都 610500

基金项目: 海南省科技重点研发项目“莺−琼盆地浅层天然气富集机理与有利勘探方向研究”（ZDYF2024GXJS031）

详细信息

作者简介:
汤翟：E-mail：tang_di@126.com

通讯作者:
E-mail：zhaojun_70@126.com

中图分类号: P631.8；P618.13
计量
- 文章访问数: 395
- PDF下载量: 25
- 被引次数: 0
出版历程
- 收稿日期: 2024-03-07
- 录用日期: 2024-05-11
- 修回日期: 2024-04-22
- 网络出版日期: 2024-05-11

Logging identification and saturation estimation method for hydrate-bearing gas layers in the deep water and ultra-shallow strata of the South China Sea

TANG Di^{1, 2
,},
PEI Jianxiang^{1, 2},
ZHAO Jun^{3
, ,},
LUO Yuhu^{1, 2},
GUO Li^{1, 2},
JIA Jiang³

1 .
Hainan Energy Co. Ltd., CNOOC (China) Co., Ltd., Haikou 570312, China
2 .
Hainan Branch, CNOOC (China) Co., Ltd., Haikou 570312, China
3 .
School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China

Funds: Supported by the Science and Technology Special Fund of Hainan Province and the Hainan Provincial Key R&D Project "Study on the Enrichment Mechanism and Favorable Exploration Directions of Shallow Gas in the Ying-Qiong Basin" (No. ZDYF2024GXJS031).

More Information

Author Bio:
E-mail：tang_di@126.com

Corresponding author: E-mail：zhaojun_70@126.com

摘要

摘要:
在海域天然气水合物的勘探过程中，含水合物气层因同时赋存天然气水合物与浅层气，电性测井响应特征异常复杂，导致其定性识别与定量评价面临较大挑战。为解决这一问题，本研究充分利用测井多物理场在水合物和浅层气中的差异响应，创新性地提出了基于纵波测井与电阻率测井多信息源的联合反演方法，以提高含水合物气层饱和度的计算精度。基于南海深水超浅层疏松砂岩含水合物气层“同增同减”的测井响应特征，综合筛选低自然伽马、低泥质含量、高孔隙度、稳定厚度的砂质层段作为储层，并结合孔隙度差值法、中子−密度曲线重叠法、剪切模量法等定性识别方法进行层位判定。随后，采用中子−密度联合法计算孔隙度，在三相Biot方程与阿尔奇公式均考虑含气饱和度的基础上，运用循环迭代法同步反演纵波速度与电阻率，优化联合误差，最终求解含水合物气层的饱和度。研究结果表明，在储层段内，通过综合运用含烃或水合物的测井指示方法，并结合流体性质判别表，可有效识别含水合物气层。含水合物气层的典型特征包括：电阻率绝对值法和正演电阻率曲线重叠法指示含烃或水合物，中子−密度曲线重叠法指示含浅层气，剪切模量高于背景值等。采用纵波与电阻率测井的联合反演方法计算含水合物气层饱和度，验证其可行性与可靠性。应用于L区块Z井的联合反演计算结果与岩心饱和度的吻合度达81.25%，L区块Y井的计算结果与单独使用水合物或浅层气计算模型的吻合度接近85%。研究成果可为现场含水合物气层的识别及饱和度计算提供重要参考，为深水区域水合物资源的精细化评价奠定技术基础。
- 含水合物气层 /
- 水合物 /
- 浅层气 /
- 测井响应特征 /
- 饱和度计算 /
- 声电联合反演 /
- 南海
Abstract: Objective
In marine natural gas hydrate exploration, hydrate-bearing gas layers−simultaneously containing natural gas hydrates and shallow gas−exhibit extremely complex electrical logging responses. This complexity poses significant challenges for both qualitative identification and quantitative evaluation.
Methods
To address this issue, this study fully leverages the differential responses of multi-physical logging in hydrates and shallow gas occurrences and proposes a novel joint inversion method based on multi-source information from P-wave logging and resistivity logging to improve the accuracy of hydrate-bearing gas layer saturation calculations. Guided by the "synchronous increase and decrease" logging response characteristics of hydrate-bearing gas layers in ultra-shallow unconsolidated sandstone reservoirs of the South China Sea, sandy intervals with low natural gamma, low shale content, high porosity, and stable thickness were comprehensively selected as reservoir layers. Qualitative identification was performed using porosity difference method, neutron-density curve overlap method, and shear modulus method. The neutron-density crossplot technique was employed to determine porosity, and by incorporating gas saturation into the three-phase Biot equation and Archie's formula, a cyclic iterative inversion method was used to simultaneously estimate P-wave velocity and resistivity, optimizing joint errors and ultimately solve for saturation of gas-hydrate-bearing layers.
Results
Within the identified reservoir intervals, hydrate-bearing gas layers can be effectively distinguished by combining hydrocarbon or hydrate indicators from absolute resistivity method and the synthetic resistivity curve overlap method, neutron-density crossplots for shallow gas indications, and elevated shear-modulus values relative to the background. The joint inversion method integrating sonic and resistivity logging is feasible and reliable for calculating hydrate-bearing gas layer saturation. Applied to Well Z in Block L, the joint inversion yielded an 81.25% match with core-derived saturation. For Well Y in Block L, agreement between the joint inversion results and independent hydrate or shallow gas saturation models was approximately 85%.
Conclusion
The study provides critical insights into the identification and estimation of the saturation of in-situ gas-hydrate-bearing layers, laying a technical foundation for the refined evaluation of hydrate resources in deepwater areas.
- hydrate-bearing gas layer /
- hydrate /
- shallow gas /
- logging response characteristics /
- saturation calculation /
- acoustic and electric joint inversion /
- South China Sea

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图 1 含水合物气层测井参数交会图

Figure 1. Crossplot of log parameters for hydrate-bearing gas layer

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图 2 L区块X井三相混合层声电响应特征图（1 in=25.4 mm，下同）

Figure 2. Acoustic-electric response characteristics of three-phase mixed layer in Well X, Block L

下载: 全尺寸图片幻灯片

图 3 L区块含水合物气层测井识别图（a. X井；b. Y井. 电阻率单位为Ω·m；中子单位为%；密度单位为g/cm³；剪切模量单位为GPa；下同）

Figure 3. Logging-based identification diagram of hydrate-bearing gas layer in Block L

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图 4 纵波和电阻率测井联合反演计算饱和度流程图

V_iv. 反演的纵波速度；V_p. 测井纵波速度；R_iv. 反演的电阻率；R_t. 测井电阻率

Figure 4. Flowchart of joint inversion calculation of saturation using P-wave logging and resistivity logging

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图 5 L区块取样的糊状(a)和块状(b)泥砂样品

Figure 5. Viscous (a) and granular (b) mud and sand samples collected in Block L

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图 6 L区块阿尔奇公式系数交会图

Figure 6. Crossplot of Archie coefficients in Block L

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图 7 L区综合解释成果图（a. Z井；b. X井；c. Y井）

Figure 7. Comprehensive interpretation map of Block L

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表 1 琼东南盆地L区块含水合物气层测井参数统计结果

Table 1. Statistical results of logging parameters for gas hydrate reservoir in Block L, Southeast Qiongdong Basin

流体性质	自然伽马/ GAPI	电阻率/ (Ω·m)	中子孔隙度/ %	纵波时差/ (μs·ft⁻¹)	密度/ (g·cm⁻³)
水层	83	1.5	57	175	2.02
	85	1.6	56	178	2.02
	81	1.7	49	176	2.04
	84	1.6	56	175	2.09
	85	1.6	52	178	2.07
	83	1.6	61	177	2.12
	83	1.8	61	172	2.05
水合物层	81	2.6	55	136	1.99
	82	2.9	69	168	1.98
	82	2.8	66	168	2.02
	83	3.5	71	124	1.97
	82	3.8	71	114	1.98
	83	4.0	64	132	2.01
	83	2.9	78	137	2.02
含水合物气层	78	1.8	55	164	1.91
	90	1.9	52	187	1.91
	85	2.1	49	192	1.92
	78	4.1	48	202	1.93
	78	4.4	49	206	1.97
	74	2.6	50	196	1.87
	73	2.3	50	179	1.9
浅层气层	81	2.2	46	179	1.83
	78	2.0	42	180	1.76
	81	1.9	40	172	1.77
	79	1.9	40	178	1.69
	80	1.9	39	182	1.69
	81	2.0	39	181	1.67
	85	1.9	38	181	1.69
注：1 ft=12 in=0.3048 m，下同

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表 2 基于电阻率特征的流体性质判别

Table 2. Discrimination of fluid properties based on resistivity characteristics

电阻率	$ {\mathbf{\varphi }}_{\rm{s}}-{\mathbf{\varphi }}_{\rm{w}} $	$ {\mathbf{\varphi }}_{\rm{D}}-{\mathbf{\varphi }}_{\rm{w}} $	T_Z−T_J	G_z−G_b	判别结果
不变	=0	=0	≤0	=0	水层
增大	<0	≈0	≤0	>0	水合物层
增大	<0	>0	>0	>0	含水合物气层	水合物＞浅层气
	≈0	>0				水合物≈浅层气
	>0	>0				水合物＜浅层气
增大	>>0	>>0	>0	=0	浅层气层
注：$\varphi_{\mathrm{s}} $. 纵波计算孔隙度；φ_w. 含水孔隙度；φ_D. 密度计算孔隙度；T_Z. 中子孔隙度；T_J. 中子孔隙度基值；G_z. 剪切模量；G_b. 剪切模量背景值

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表 3 井下泥砂样品信息

Table 3. Subsurface sand and mud samples information

序号	井深/m	黏土	石盐	石英	钾长石	斜长石	方解石	白云石
序号	井深/m	φ_B/%
1	1651.5	42.1	2.0	31.4	4.7	5.6	14.3	0
2	1653.6	30.2	0.9	23.5	29.2	4.7	11.5	0
3	1724.4	33.1	0	38.9	4.3	13.3	7.0	3.4
4	1728.4	41.0	0	33.6	3.2	11.4	7.6	3.1

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表 4 琼东南盆地L区Z井含水合物气层饱和度预测结果对比

Table 4. Comparison of predicted saturation in the hydrate-bearing gas layer for Well Z, Block L, Qiongdongnan Basin

序号	深度/m	水合物饱和度预测值/%	岩心实测饱和度/%	误差值/%
1	1630.51	35.2	35.3	0.1
2	1632.34	33.4	33.6	0.2
3	1646.53	19.8	31.3	11.5
4	1647.35	21.2	22.1	0.1
5	1649.59	33.2	33.2	0
6	1650.82	42.2	32.6	9.6
7	1653.82	30.1	30.0	0.1
8	1654.62	22.4	22.3	0.1
9	1655.12	16.8	22.1	5.3
10	1668.92	31.3	30.9	0.4
11	1670.21	28.9	29.1	0.2
12	1671.59	25.9	25.8	0.1
13	1674.21	31.3	31.5	0.2
14	1675.11	29.9	30.2	0.3
15	1677.53	27.9	28.4	0.5
16	1707.26	18.2	18.5	0.3

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