收稿日期: 2010-02-03
修回日期: 2010-08-29
网络出版日期: 2011-06-10
Application of Gas-recognition Technology Based on Wavelet Decomposition to Shallow Gas Reservoir Exploration
Received date: 2010-02-03
Revised date: 2010-08-29
Online published: 2011-06-10
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。
高倩, 李仲东, 赵爽 . 基于子波分解的含气性识别技术在CC地区浅层气藏勘探中的应用[J]. 天然气地球科学, 2011 , 22(3) : 549 -553 . DOI: 10.11764/j.issn.1672-1926.2011.03.549
We use the wavelet decomposition technology to resolve the conventional seismic data track into a collection of different frequency wavelets, and then check the gas-bearing reservoirs based on the spectrum anomaly detection. The Shaximiao sequence as an objective layer of CC area is a set of river-delta deposits with a single-storey sandstone thickness about 20 m. The reservoirs in the similar river in the different locations and the similar position in the different rivers have the different gas concentration. The traditional spectrum technology of seismic data is restrained by the window restriction so that the antinoise and poor stability can not accurately identify the gas-bearing. In order to predict the gas bearing areas in the different times and different locations, we firstly try to use the gas-recognition technology of wavelet decomposition to get the abnormal frequency spectrum. The gas-bearing river sandstones have the feature of “low-frequency resonance, high frequency attenuation”. We use this feature not only to clearly test the distinction between current high-yield well and dry well, but also to provide a evidence for the further plot of drilling wells.
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