Gas hydrate reservoir types, characteristics and development methods
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摘要: 天然气水合物作为潜能巨大、资源量丰富、燃烧值高的未来新能源，但由于其特殊的物理力学性质和赋存状态，经济开采技术仍面临诸多难题。本文以全球勘探发现存在天然气水合物的地区为基础，介绍了全球主要水合物的海陆资源分布及开采难易程度；以主要影响天然气水合物开采方式选择因素为基础，分析了天然气水合物在地层中的赋存类型、成藏模式和储层分类方法；以全球已开展的天然气水合物试采项目为基础，对比分析了现有多种天然气水合物开采方法的优缺点和适用条件；在现有开采方法条件下，为不同赋存状态、成藏模式和储层分类的天然气水合物选择出适合的开采方法，为建立完整的天然气水合物开采技术体系和未来实现商业化开采提供参考。Abstract: Natural gas hydrate is a new type of energy with huge resource potential and high combustion value. Due to its special occurrence and physical-mechanical properties, economic development of the resources still faces many problems and challenges. The distribution patterns of gas hydrate resources in the sea and on the land as well as the difficulties ever encountered in the exploitation of some major hydrate deposits in the world are studied in this paper as cases. Based on the mining methods selected, the occurrence, accumulation models and reservoir classification of gas hydrate underground are analyzed and discussed. Taking some pilot hydrate production projects as examples, various existing natural gas hydrate mining methods are compared and analyzed for their advantages, disadvantages and application feasibilities. Based upon the above discussion, suitable mining methods are selected and recommended. The paper may provide a reference for establishing a complete natural gas hydrate mining technology system for realization of commercial exploitation in the future.
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Keywords:
- natural gas hydrate /
- occurrence type /
- accumulation mode /
- reservoir classification /
- mining method
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天然气水合物是一种笼状结构的类冰状结晶化合物，主要是由甲烷和水分子结合而成，因其在冻土地区和海洋大陆边缘广泛分布、与海底稳定性相关，以及可能对全球气候具有潜在影响而广受关注[1-2]。新西兰Hikurangi大陆边缘每两年左右发生一次慢滑移事件[3]，有关证据显示，多期次水合物形成分解可能是造成该区产生蠕变的重要原因之一[4]。
2017年11月—2018年1月执行了“蠕变中的天然气水合物滑动和Hikurangi随钻测井”为主旨的IODP372航次。该航次的主要目的之一是调查天然气水合物和海底滑坡的关系，因此，在新西兰Hikurangi边缘Tuaheni滑坡复合体（Tuaheni Landslide Complex，TLC）的U1517站位进行了随钻测井工作（图1）。该站位钻井的主要任务是通过在滑坡体和天然气水合物稳定区进行测井和采样，研究水合物与蠕变的关系。
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20世纪末，研究人员在新西兰Hikurangi边缘发现地震高振幅异常和似海底反射（BSR）标志[4-7]。该区域反射地震[8-11]、电磁[12-14]、甲烷渗漏、海水甲烷浓度、与渗漏相关的沉积坍塌和冷泉等证据均指示有天然气水合物存在[15-19]。通过反射地震发现，Hikurangi大陆边缘的Tuaheni滑坡复合体显示了活动蠕变变形的特征，且蠕变中的近陆边缘与海底天然气水合物稳定带底部的尖灭相一致[4]，因此，科学家认为水合物分解—形成过程可能与新西兰Hikurangi边缘的多期次慢滑移密切相关[4, 20-21]。TLC地区水合物分布和含量估算是研究蠕变与水合物关系的必要环节。Mountjoy提出3种机制解释浅层天然气水合物是如何导致慢滑移，主要认为是由于水合物的分解导致沉积物液化失稳、水合物分解对地层孔隙压力的影响和水合物含量对地层提供的不同支撑模式的影响[4]。不同饱和度的水合物对沉积物的支撑模式不同[22]，因此，准确估算慢滑移区域水合物的饱和度可以进一步分析天然气水合物导致TLC慢滑移的原因，IODP372航次测井和取心为水合物饱和度估算提供了可靠资料。
由于声速和电阻率对水合物储层最为敏感，常用声学、电学模型来估算天然气水合物饱和度[23-24]。基于电阻率的模型有阿尔奇方程[25]和连通性方程[26]；基于声速的模型有权重方程（Weighted equation，WE）[27]、等效介质理论（Effective Media Theory，EMT）模型[28]、改进的Biot-Gassmann理论（Biot-Gassmann Theory by Lee，BGTL）模型[29-30]和简化三相介质方程（Simplified Three-Phase Equation，STPE）[31]等，其中，常用于测井应用的模型主要是STPE和等效介质理论[32]两种。由于STPE模型参数较易获取，所以多次被实际应用于估算天然气水合物饱和度，均得到理想的预测效果[33-34]；Hu等采用超声探测技术和时域反射技术实时探测了沉积物的纵横波速度和水合物饱和度的变化情况，检验了多种理论模型，发现BGTL理论预测的纵、横波速度更接近实测值[35]，但BGTL模型中与岩石固结程度相关参数难以通过实际地层数据计算，从而导致较少被应用于测井数据估算水合物饱和度。本文主要通过STPE与BGTL模型对U1517站位水合物饱和度进行研究，在BGTL模型使用新的参数选取方法，使参数获取更为简易，计算过程中，根据岩性划分不同层段对应的矿物成分含量，用于纵波速度模型计算，以精确模型判断水合物储层深度分布和天然气水合物饱和度计算。
1. 测井数据分析
IODP372航次U1517站位测井位于38°S、178°E（图1），井深约205 mbsf。该航次通过随钻测井采集了井径、声波速度、伽马密度、孔隙度、自然伽马和电阻率等数据，其中纵波数据在160～168 mbsf层段内未获取。通过对LDEO（Lamont Doherty Earth Observatory）数据库提供的U1517站位原始测井数据进行解释分析，并拟合背景趋势线，结果如图2所示，实测纵波声速与背景拟合声速相比，速度增加出现在94～160 mbsf层段，氯离子浓度异常出现在104～160 mbsf层段；在94～104 mbsf层段纵波速度和孔隙度等明显增加，而电阻率与密度减小，氯离子浓度并无异常，该层段的异常与21～28 mbsf层段相似，可能为井孔和局部岩性变化造成（图中黄色区域）。天然气水合物稳定区大概位于104～160 mbsf，并且在130～145 mbsf层段（图中绿色区域），纵波速度、电阻率和井径明显增加，密度减小。该航次从U1517站位获得多个柱状样品，使用红外热像仪进行扫描，温度异常表明天然气水合物的存在，并发现在岩心的上层沉积物或其岩心采集器中有甲烷释放[37]。图3所示为地层因子与纵波速度交会图，由于含天然气水合物的沉积物具有较高的纵波速度和地层因子，所以含天然气水合物的沉积地层的交会图显示高于饱和水沉积地层[34]，在130～145 mbsf层段显示较高的地层因子和纵波速度。
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图 2 U1517站位测井数据蓝色实线为实测数据，红色实线为拟合背景趋势，黑色虚线为BSR。Figure 2. Well logs at Site U1517The blue lines are measured logging data and the red lines are fitted background trends; the black dashed line is BSR.![]()
图 3 U1517站位井地层因子与纵波速度交会图黑色实线为0～90 mbsf拟合背景趋势线。Figure 3. Cross plot of formation factor versus the measured P-wave velocities at Site U1517The black line is fitted background trends of 0～90 mbsf.2. 储层水合物饱和度估算
依据国际大洋发现计划出版物（International Ocean Discovery Program Publications）[36]获取矿物类型及含量数据，基于该数据，根据岩性划分不同层段对应的矿物成分含量，结果如图4所示，用于纵波速度模型计算，以精确天然气水合物饱和度计算值。岩石骨架的不同矿物类型的物性参数如表1所示。
表 1 骨架组分及物性参数Table 1. Constants used for the modeling![]()
图 4 U1517站位所取岩心的岩性和岩石矿物成分相对含量数据黑线为依据岩性平均矿物成分相对含量。Figure 4. Simplified lithostratigraphic column with bulk powder XRD results, Site U1517Black line is average mineral composition based on core data.2.1 简化三相介质模型（STPE）
含天然气水合物储层具有相对较高的纵横波速度。本次研究中使用STPE模拟U1517站位井的纵波速度，其中用于纵波速度（Vp）建模的STPE[31, 33]使用等式（1）对水合物储层的纵波速度建模：
$${V_{\rm{p}}} = \sqrt {\frac{{k + {\rm{4}}\mu /{\rm{3}}}}{\rho }} , \; {V_{\rm{s}}} = \sqrt {\frac{\mu }{\rho }} $$ (1) 式中ρ是含天然气水合物沉积模型的体积密度，k是体积模量，μ是剪切模量。建模参数ε是解释在加强主体沉积物骨架方面天然气水合物形成相对于压实的影响减小，Lee和Waite推荐使用ε=0.12为建模数值[30]。在Vp和Vs建模中使用的参数α使用等式（2）计算：
$${\alpha _{\rm{i}}} = {\alpha _0}{({p_0}/{p_i})^{\rm{n}}} \approx {\alpha _0}{({d_0}/{d_{\rm{i}}})^{\rm{n}}}$$ (2) 式中α0是有效压力p0和深度d0的固结参数，αi是有效压力pi和深度di的固结参数，固结参数可以使用饱和水沉积物的速度来估算[40]。固结参数取决于固结程度和该区域的有效压力，Mindlin认为体积模和剪切模量为有效压力的1/3幂[41]，因此不同位置，根据研究区域的主要岩性，α的值随深度而变化[40]。通过建模速度基线和实测纵波速度之间的最佳拟合选定α的值[40]，本次研究用于U1517站位井的固结参数αi=42（60/di）1/3。使用上述参数，获得了井下剖面背景纵波速度和天然气水合物饱和度，饱和水沉积地层VP符合程度较高（图5，图6），黑色实线为航次实测纵波速度，红色实线为本文利用STPE模型计算结果，如图5所示，104～160 mbsf层段内测井实测VP大于理论基线速度，可能属于天然气水合物储层区，利用航次实测数据和模型结果计算出水合物饱和度（图6）。结果显示，在104～160 mbsf的深度区间内平均饱和度约为5.2%，最高饱和度达到22.7%，其中130～145 mbsf层段内水合物饱和度较高，平均饱和度为7.9%。
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图 5 使用STPE在U1517站位井测量的纵波速度和计算的基线速度的比较Figure 5. Measured and calculated baseline P-wave velocities with STPE at the Site U1517![]()
图 6 使用STPE计算水合物储层区的背景纵波速度及饱和度Figure 6. Measured and calculated baseline resistivities and P-wave velocities at the Site U15172.2 改进的Biot-Gassmann模型（BGTL）
BGTL理论建立在经典的BGT理论（Biot-Gassmann Theory）上，在预测速度时不仅考虑了分压的影响，而且还考虑了岩石的孔隙度、固结度等因素的影响[35]。在BGTL模型计算中，将天然气水合物作为基质中的一种矿物成分。本研究用于VP建模的BGTL模型使用等式（1）进行。
公式（1）中沉积介质的剪切模量μ可由下式计算：
$$ \mu=\frac{\mu_{\rm{ma}}{ G}^2\left(1-\varPhi\right)^{2{ n}}{ k}}{{{k_{\rm{ma}}}}+4\mu_{\rm{ma}}\left[1-{ G}^2\left(1-\varPhi\right)^{2{ n}}\right]/3} $$ (3) 式中，kma为岩石骨架的体积模量；μma为岩石骨架的剪切模量；Φ为孔隙度；常数G主要用来校正由基质中的黏土引起的差异。Han等通过实验室数据表明G = 1对清洁砂岩有利[42]，随着黏土体积增加，G将按下式（4）计算减少：
$${{G}} = 0.955\;2 + 0.044\;8{{\rm{e}}^{ - {C_{\rm{v}}}{\rm{/}}0.067\;14}}$$ (4) 式中，泥质含量Cv可使用来自U1517A井的伽马射线测井数据通过公式（5）[34]估算：
$${C_{\rm{v}}} = 0.083({2^{{\rm{GCUR}} \times {{\rm{I}}_{{\rm{GR}}}}}} - 1)$$ (5) 式中，GCUR是与地层有关的经验系数，新地层(古新近系地层)GCUR=3.7[43]，IGR为通过伽马测井数据计算的伽马射线指数，可由公式（6）计算：
$${{\rm{I}}_{{\rm{GR}}}} = \frac{{{\rm{G}}{{\rm{R}}_{{\rm{log}}}} - {\rm{G}}{{\rm{R}}_{{\rm{min}}}}}}{{{\rm{G}}{{\rm{R}}_{{\rm{max}}}} - {\rm{G}}{{\rm{R}}_{{\rm{min}}}}}}$$ (6) 式中，GRlog为测井伽马值，GRmin为砂岩层伽马值，GRmax为泥岩层伽马值。
公式（3）中参数n取决于分压大小及岩石的固结程度，可由公式（7）得到：
$${{n}} = [{\rm{1}}{{\rm{0}}^{({\rm{0}}.{\rm{426}} - {\rm{0}}.{\rm{235Log10}}p)}}]{{/m}}$$ (7) 测量数据表明m≈5适合于固结沉积物，m≈1.5适用于疏松沉积物[29]；如图7所示利用BGTL预测饱和水沉积地层段（0～90 mbsf）速度和实测纵波速度对比，其中使用P=8.0 MPa和CV=58%，改变m值预测速度，在高孔隙度低纵波速度时m=2.5预测速度拟合程度高，而在低孔隙度高声速时，m值应小于2.5，大于1。在可能含天然气水合物地层（104～160 mbsf）的中子孔隙度主要为45%～65%，因此，本次研究建模使用m=2.5。
使用上述参数，获得了井下剖面背景纵波速度和天然气水合物饱和度（图8，图9），如图所示，黑色实线为航次实测纵波速度，红色实线为本文使用BGTL模型计算结果，绿色区域为利用航次实测与模型速度计算的水合物饱和度，104～160 mbsf层段内测井实测VP大于理论饱和水背景VP，可能属于水合物储层区，因此导出水合物饱和度。结果显示，在104～160 mbsf的深度区间内平均饱和度约为6.0%，最高饱和度达到21.6%，其中130～145 mbsf层段内平均水合物饱和度为8.5%。
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图 8 使用BGTL模型在U1517站位井测量的纵波速度和计算的基线速度比较Figure 8. Measured and calculated baseline P-wave velocities with BGTL at the Site U1517![]()
图 9 使用BGTL模型计算水合物储层区的背景纵波速度及饱和度Figure 9. Background P-wave velocities and gas hydrate saturations at Site U1517 with BGTL3. 讨论
图10为U1517站位井在104～160 mbsf层段的测井曲线，通过测井数据和背景基线看出存在3层纵波速度和电阻率明显异常的含水合物层段，同时，井径、密度和伽马测井数据均有不同程度的异常。在112～114 mbsf层段，环电阻率和声波速度明显增加，最高峰值分别为9.25 Ω·m和1.79 km/s，可能为含天然气水合物的薄层；在130～145 mbsf层段，环电阻率和声波速度最高峰值分别为2.88 Ω·m和1.90 km/s，属于较厚层的含水合物区域；在150～160 mbsf层段，密度与自然伽马降低较为明显，环电阻率和声波速度最高峰值分别为1.97 Ω·m和1.83 km/s。
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图 10 U1517站位井井径、纵波速度、电阻率、密度和伽马测井曲线Vp为实测声波速度，Vpw为背景速度值；Rt-Ring为环电阻率；Rt-P40L为低频随钻相移电阻；R0为背景电阻率值。Figure 10. The well logs from site U1517A showing the caliper, P-wave velocity, resistivity, density and gamma rayVp is measured velocity, Vpw is calculated velocity baseline, Rt-Ring is ring resistivity, Rt-P40L is 400 kHz phasor resistivity, R0 is calculated resistivity baseline.如图11所示，由纵波速度数据通过STPE和BGTL模型估算了U1517站位井104～160 mbsf层段的天然气水合物饱和度，并与IODP372航次科学家利用阿尔奇公式和氯离子浓度两种方法计算结果相比较。STPE、BGTL和航次科学家利用阿尔奇公式3种模型在104～160 mbsf层段计算的平均饱和度分别为5.2%、6.0%和6.5%，130～145 mbsf层段的平均饱和度分别为7.9%、8.5%和9.6%；130～145 mbsf层段符合航次科学家使用氯离子浓度含量估算的高饱和度层段。112～114 mbsf和130～145 mbsf层段，阿尔奇公式估算的最高饱和度分别为56%和49%，大于BGTL和STPE计算结果，但是电阻率识别高饱和度薄层水合物约为2～5 cm，而声波测井分辨率约为15 cm，该薄层饱和度异常可能由于声波测井无法探测到而引起的，同时井径也发生变化，可能影响随钻测井速度与电阻率。氯离子异常在局部地层出现异常高值，从岩心分析看，异常高值与薄砂层相对应。因此，在104～160 mbsf层段3种方法估算的饱和度随深度变化相似，表明不同测井数据之间差异不大，且天然气水合物平均饱和度最高的层段为130～145 mbsf。使用STPE和BGTL模型计算的饱和水地层（0～90 mbsf）的纵波速度与实测纵波速度比较见图12所示，对于U1517井BGTL模型比STPE模型更适用于该站位水合物饱和度估算。
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图 11 根据BGTL、STPE与电阻率、氯离子估算的天然气水合物饱和度的对比Figure 11. The gas hydrate saturation calculated by BGTL, STPE compared with the hydrate saturation calculated by the Expedition 372 scientists used the Archie equation and the chloride concentration![]()
图 12 STPE与BGTL在饱和水地层（0～90 mbsf）预测纵波速度与实测纵波速度对比Figure 12. The measured P-wave velocity compared with the calculated results of the STPE and BGTL in water-saturated sediments (0～90 mbsf)4. 结论
（1）通过U1517站位随钻测井和岩心数据综合分析，证实了该站位黏土质粉砂岩性不同层位存在天然气水合物，水合物呈层状分布。天然气水合物储层区域在104～160 mbsf层段，其中存在3层纵波速度和电阻率明显异常的含水合物层段（112～114、130～145和150～160 mbsf），112～114 mbsf层段可能为薄的天然气水合物层，而130～145 mbsf层段相较于其他层段水合物饱和度相对较高。其中112～114 mbsf层段天然气水合物饱和度最高，130～145 mbsf层段为主要天然气水合物赋存区域。
（2）依据LWD和取心数据，在计算过程中，根据岩性划分不同井段对应的矿物成分含量，用于纵波速度模型计算，并使用饱和水地层孔隙度与纵波速度拟合得到BGTL模型参数的方法，使BGTL模型更便于应用到测井资料估算水合物饱和度，通过STPE和BGTL模型计算出了U1517站位的水合物饱和度，并比较分析两种模型在饱和水地层的预测与实测纵波速度表明BGTL拟合度高于STPE；计算结果与航次科学家估算的饱和度相比，平均饱和度相近，3种方法计算的水合物饱和度值随深度变化相似，表明计算结果的合理性。
致谢：本研究所用样品和数据由IODP372航次提供，中国IODP办公室提供了胡高伟参加航次的旅费资助，在此一并致谢！
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图 3 不同天然气水合物系统的组成原理[55]
a. 水合物充填脉状网，b. 大的水合物透镜体，c. 在海洋砂中颗粒充填水合物，d. 大的海底丘，e. 在海洋黏土中孔隙充填水合物，f. 在陆地北极地区砂岩或砾岩中孔隙充填水合物。
Figure 3. Occurrence of different gas hydrate systems[55]
a. networks of hydrate-filled veins, b. massive hydrate lenses, c. grain-filling methane hydrate in marine sands, d. massive sea-floor mounds, e. grain-filling methane hydrate in marine clays, f. grain-filling methane hydrate in onshore Arctic sands/conglomerates.
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图 8 化学抑制剂注入法示意图
Figure 8. The schematic diagram of chemical inhibitor injection method
表 1 全世界主要的陆地冻土和海域水合物分布带[31]
Table 1 Major marine and land gas hydrate distribution zones in the world[31]
类型 地理位置 埋藏深度及分布范围 勘探及试采地点 陆地冻土
水合物麦索雅哈河流域至西伯利亚北部区域 水合物埋藏深度为300～1 000 m，分布面积为1 700×106 km2。 麦索雅哈气田 普拉德霍湾至阿拉斯加北坡区域 水合物埋藏深度为210～950 m，阿拉斯加北坡砂质储层的平均资源量为 2.4万亿m3 [32] 普拉德霍湾气田Ignik Sikumi项目；Mount Elbert地质探井 麦肯齐三角洲盆地及北极区域 水合物埋藏深度为200 m以下，水合物储量约为0.01～1万亿m3，潜在的甲烷储量大约为1～100万亿m3[29] 麦肯齐三角洲理查德岛的Mallik区块 青藏高原永久冻土区域 水合物埋藏在永久冻土层之下133～396 m，冻土面积达215×104 km2[33] 祁连山永久冻土区钻井 海域水合物 北冰洋的水合物生成带 水合物分布在北极大陆架90 m水深至海底的永久冻土带 加拿大北极岛 大西洋的水合物生成带 布莱克海脊（水合物矿床厚度约20 m，原地资源量超28万亿m3[34]）、墨西哥湾（水合物埋深泥线以下500～1 000 m区域）、加勒比海、斯匹次卑尔根岛边缘、几内亚湾（水合物水深超过1 200 m，总覆盖面积达到
35 000 km2的区域[35]）东海岸布莱克海台大洋钻探、墨西哥湾近海勘探、西非喀麦隆近海勘查 太平洋的水合物生成带 中国南海（水合物资源量估算值为6.3×1013 m3，其中南海北部陆坡资源量为4.0×1013 m3[36]）、日本南海海槽（水合物面积为7 000 km2，原地气资源量平均估算值约1.1万亿m3[37]）、韩国东海郁陵盆地（存在大量水合物“气烟囱”构造，水合物矿床可能藏有1.2亿t的碳[14]）、新西兰希库朗伊海槽（水合物中估计含有5～11万亿m3甲烷[38]）、白令海、鄂霍茨克海、中美洲海槽、北加利福尼亚俄勒冈近海、秘鲁海槽 神狐海域、Nankai海槽、Ulleung盆地、鄂霍茨克海千岛盆地 印度洋的水合物生成带 印度半岛近海（水合物的存在区域约1.5 km2[39]）、孟加拉湾、阿拉伯海（水合物沉积面积约80000 km2）、阿曼湾（水合物层稳定存在于350～700 m的沉积物层） Krishna Godavari盆地、Makran Margin 陆地内海的水合物生成带 黑海（水合物层厚度为160～500 m，分布面积约为3.0×104 km2，总量约为42×1012 m3）、里海（水合物层位于海床下390～480 m，厚度约为134～152 m[40-41]）、亚速海盆地、贝加尔湖（水合物资源量估算相当于（0.88～9）×1012 m3的天然气[42]） Crimea、Caucasus、贝加尔湖 
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表 2 全世界主要的水合物勘探区水合物藏的特征和主要开采方法
Table 2 Characteristics and main mining methods of hydrate reservoirs in major hydrate exploration areas around the world
类型 勘探区域 储层岩性 赋存类型 成藏模式 主要开采方法 陆地冻土水合物 俄罗斯麦索雅哈气田 砂岩 孔隙充填型 成岩型 降压法 美国阿拉斯加北坡冻土带 砂岩 孔隙充填型 成岩型 降压法 加拿大麦肯齐三角洲盆地 砂岩、砾岩 孔隙充填型 成岩型 降压法 中国祁连山永久冻土带 泥岩、粉砂岩 孔隙充填型，块状、层状 成岩型 降压法结合置换法 海域水合物 中国南海神狐海域 粉沙质黏土、含粉沙黏土 孔隙充填型，脉状、结节状 构造型 置换法结合降压法 美国布莱克海脊 黏土质粉砂、粉砂质黏土 孔隙充填型，极少数块状、结节状、层状、脉状 构造型 置换法结合降压法 美国墨西哥湾 火山碎屑砂岩、砂岩夹泥等细粒沉积物 孔隙充填型，部分裂隙充填型 构造型 置换法结合降压法 日本南海海槽 粉沙质沙、黏土质粉沙 孔隙充填型 构造型 置换法结合降压法 韩国郁陵盆地 黏土质粉砂岩、砂质粉砂岩、粉砂质砂岩 裂隙充填型，部分孔隙充填型，少数块状 构造型 置换法结合降压法 印度近海 粉砂质黏土 裂隙充填型 复合型 降压法结合置换法
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