Gas hydrates that exist in the subsurface are often difficult to detect with reflection seismic data if the seismic data lacks a strong bottom simulating reflection (BSR). In these cases, the imaging and detection of the gas hydrate stability zone (GHSZ) becomes particularly difficult, as hydrate detection relies heavily on the BSR, gas chimneys, or pockmarks on the seafloor. To address and improve upon these imaging complications, an unsupervised machine learning multi-attribute analysis is performed on 2D seismic data in the Pegasus Basin in New Zealand where the BSR is not continuously or clearly imaged. Rock physics analysis has demonstrated that the inclusion of methane gas hydrates in the pore space results in a slightly increasing amplitude at the base of the gas hydrate zone, regardless of the fluid (brine or gas) in the pore space below the hydrates. This increasing amplitude is quite weak and can be masked by noise. In the scenarios where a strong seismic impedance difference is lacking, a BSR is not typically observed in the seismic data, even though gas hydrates do exist in the subsurface. To enhance the detection of the presence of gas hydrates, a multi-attribute analysis is performed with a series of seismic attributes that can detect the minute changes in the seismic waveform due to the presence of gas hydrates. The successful attributes are those that are sensitive to attenuation, frequency, and small amplitude anomalies.

如果地震数据缺乏强烈的底部模拟反射（BSR），则通常难以通过反射地震数据检测地下存在的天然气水合物。在这些情况下，由于水合物检测严重依赖于BSR，气体烟囱或海底的浮标，因此对气体水合物稳定区（GHSZ）的成像和检测变得特别困难。为了解决和改善这些成像并发症，对新西兰飞马盆地的2D地震数据进行了无监督的机器学习多属性分析，在该数据中BSR不能连续或清晰地成像。岩石物理分析表明，孔隙空间中包含甲烷水合物，导致天然气水合物带底部的振幅略有增加，不管水合物下方孔隙中的流体（盐水还是气体）。这种增加的幅度非常弱，并且可以被噪声掩盖。在缺少强地震阻抗差的情况下，即使地下存在气体水合物，在地震数据中也通常不会观察到BSR。为了增强对天然气水合物存在的检测，使用一系列地震属性进行多属性分析，这些属性可以检测由于天然气水合物存在而引起的地震波形的微小变化。成功的属性是对衰减，频率和小幅度异常敏感的属性。即使在地下存在气体水合物，通常也不会在地震数据中观察到BSR。为了增强对天然气水合物存在的检测，使用一系列地震属性进行多属性分析，这些属性可以检测由于天然气水合物存在而引起的地震波形的微小变化。成功的属性是对衰减，频率和小幅度异常敏感的属性。即使在地下存在气体水合物，通常也不会在地震数据中观察到BSR。为了增强对天然气水合物存在的检测，使用一系列地震属性进行多属性分析，这些属性可以检测由于天然气水合物存在而引起的地震波形的微小变化。成功的属性是对衰减，频率和小幅度异常敏感的属性。