Using recursive inversion as input for gross-rock volume extraction from lithology prediction volumes: How bad can it be?

J. Shadlow
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Abstract

Summary Reserves and Resources can be directly estimated by using seismic lithology prediction volumes generated from AVO inversion, calibrated to wells, to estimate sand rock volumes within a stratigraphic interval. However, high quality AVO inversion data and studies are not always available. This case study utilises recursive inversion to generate prediction cubes for input to geobody based gross rock volume estimates. Here, relative recursive inversions of the near and far seismic stacks are generated. EEI rotation theory was applied to calculate relative AI and Vp/Vs volumes. These have then been converted to band-limited absolute inversion volumes by adding a low frequency model built using seismic horizons, well logs and rock physics trends. Finally, probability density functions calibrated to wells were estimated to calculate lithology prediction volumes. A sand probability volume is then calculated using these probability density functions. A relative approach has not been applied due to poor separability of different lithologies in cross-plot space. This method is applied to an area where a single multiazimuth PSDM seismic survey covers two gas fields and several deep exploration prospects. However, previous inversion studies were limited to the individual fields (each inverted separately), incorporated fluid contact information and did not cover the deeper exploration, so were therefore considered sub-optimal. Although there is potential for results from this method to be “bad”, this case study was successful. The inversion volumes generated as part of this study enabled a wholistic view of the fields and exploration prospectivity, which had not been previously possible with the available QI volumes. The seismic data used for input was exceptionally good, and there was abundant well control to provide control and for use in blind testing. The amount of validation and quality-control applied to this project cannot be under-stated. It is critically important to be mindful of the limitations and broad assumptions that are applied as part of this work-flow. These include the addition of the low-frequency model, wavelet affects not being taken into account and depth decay of the lithology predictions due to the application of a single PDF.
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用递归反演作为输入从岩性预测卷中提取总岩体体积:它能有多差?
利用AVO反演产生的地震岩性预测体积,对井进行校准,可以直接估算地层段内的砂岩体积,从而估算储量和资源。然而,高质量的AVO反演数据和研究并不总是可用的。本案例研究利用递归反演生成预测立方体,用于输入基于总岩石体积估计的地质体。在这里,产生了近、远地震叠加的相对递归反演。应用EEI旋转理论计算相对AI和Vp/Vs体积。然后,通过添加利用地震层位、测井曲线和岩石物理趋势建立的低频模型,将这些数据转换为带限绝对反演体积。最后,估计校准到井的概率密度函数,以计算岩性预测体积。然后使用这些概率密度函数计算砂概率体积。由于不同岩性在交叉地块空间的可分性较差,因此没有采用相对方法。该方法应用于某地区,该地区一次多方位PSDM地震调查涵盖了两个气田和多个深部勘探前景。然而,之前的反演研究仅限于单个油田(每个油田都是单独反演的),纳入了流体接触信息,没有涵盖更深层次的勘探,因此被认为是次优的。尽管这种方法的结果有可能是“坏的”,但这个案例研究是成功的。作为本研究的一部分,生成的反演体积使我们能够全面了解油田和勘探前景,这是以前可用的QI体积所无法实现的。用于输入的地震数据非常好,并且有丰富的井控来提供控制和盲测。应用于这个项目的验证和质量控制的数量不能被低估。非常重要的是要注意作为此工作流程的一部分所应用的限制和广泛的假设。其中包括低频模型的加入,小波影响未被考虑在内,以及由于单一PDF的应用而导致的岩性预测的深度衰减。
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