Data Conditioning for a Combined Inversion and AVO Reservoir Characterisation Study

M. Silva, M. Rauch-Davies, A. S. Cuervo, P. Veeken
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引用次数: 6

Abstract

Summary The Cocuite gas field, located onshore Mexico, is producing since the 1960’s from 4 main reservoir levels (E, G, channels, M) with a steadily declining production rate. The structural interpretation indicates important extensions of the main gas accumulation, undrained by existing wells. Detailed amplitude studies are conducted, using both pre- and post-stack seismic data, to validate this hypothesis and minimise the risk in out-step drilling. A sub-volume of 100 km 2 from the Cocuite 3D seismic survey was reprocessed. The data conditioning includes a full Kirchhoff pre-stack time migration, detailed velocity analysis and special noise attenuation. The zero-phased time-migrated CDP gathers were stacked and inverted to acoustic impedance (AI) by applying a model-driven inversion algorithm. The same CDP gathers formed also input for an AVO analysis, whereby the “intercepttimes-gradient” and “fluid-factor” attributes are extracted. The complexity of the inversion and AVO results called for the generation of synthetic 1D AVO models in order to better understand the seismic response. A large number of existing wells have been examined on their AVO behaviour. The prestack seismic imaging showed a good differentiation between gas and brine filled reservoirs. A combined approach - of structural interpretation, amplitude mapping, together with the presence of anomalous AVO behaviour and a drop in acoustic impedance – is essential for reducing the drilling risk attached to new prospects. Proper data conditioning is crucial for reliable seismic imaging and gives access to quantitative interpretation of reservoir characteristics.
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结合反演和AVO油藏表征研究的数据调理
Cocuite气田位于墨西哥陆上,自20世纪60年代以来,从4个主要储层(E、G、通道、M)开始生产,产量稳步下降。构造解释表明了主要天然气聚集的重要延伸,未被现有井排水。利用叠前和叠后地震数据进行了详细的振幅研究,以验证这一假设,并将超前钻井的风险降至最低。对Cocuite三维地震调查的100 km2的子体进行了重新处理。数据调理包括一个完整的基尔霍夫叠前时间偏移,详细的速度分析和特殊的噪声衰减。采用模型驱动反演算法,对零相位时间偏移CDP集进行叠加并反演到声阻抗(AI)。形成的相同CDP聚集也用于AVO分析,从而提取“截距时间梯度”和“流体因子”属性。由于反演和AVO结果的复杂性,需要生成综合一维AVO模型,以便更好地理解地震响应。对大量现有井的AVO行为进行了研究。叠前地震成像显示气、卤水气藏具有较好的分异性。结合结构解释、振幅测绘、异常AVO行为和声阻抗下降的方法,对于降低新勘探区的钻井风险至关重要。对于可靠的地震成像和储层特征的定量解释来说,适当的数据调理是至关重要的。
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