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利用子波分解技术将常规地震数据道分解成不同频率子波的集合,并以此为基础开展基于频谱异常的储层含气性检测。CC地区目的层———沙溪庙组以一套河流—三角洲沉积为主,砂体单层厚度不大,多在20 m左右,且同一河道的不同位置以及相同位置的不同河道,其储层含气性迥异。基于传统地震数据的频谱分析由于受其分析时窗限制,其抗噪性和稳定性差,难以准确识别其含气性。为了能准确预测该地区不同期次,不同位置河道砂体的含气性,将基于子波分解的含气性识别技术加以应用,通过分析其得到的频谱异常发现,该地区含气河道砂岩具有明显的“低频共振,高频吸收衰减”特征,利用该特征不但能清晰区分当前高产井与干井,而且成为后期井位部署的主要依据。
The wavelet decomposition technique is used to decompose the conventional seismic data into a set of wavelets of different frequencies, and based on this, a gas-bearing detection of reservoir based on spectral anomalies is carried out. In the CC area, the Shaximiao Formation is dominated by a series of river-delta sediments. The monolayer thickness of the sand body is not large, mostly about 20 m. Different channel locations of the same channel and different channels of the same location, Different gas layers. Spectrum analysis based on traditional seismic data is difficult to accurately identify its gas-bearing properties due to its poor anti-noise and stability due to its time-window analysis. In order to accurately predict the gas-bearing of sand bodies in different positions and in different positions in the region, the gas-bearing identification technology based on wavelet decomposition is applied. By analyzing the spectral anomalies obtained, it is found that gas-bearing channel sandstones in this region have The obvious feature of “low frequency resonance and high frequency absorption decay” can not only distinguish the current high production well from dry well clearly, but also become the main basis for late well location.