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Abstract

Summary

Generation of seismic production forecasting models, based on integration of geological, geophysical and engineering data has proven to be a powerful tool to characterize and identify sweet spots or areas of better performance in unconventional reservoirs.

Integration of geological, geophysical and petroleum engineering data can be a difficult task because they measure differently dynamic and static properties of reservoirs components with very different sampling metrics and units. Traditional multidisciplinary workflows accepted by the industry are very lengthy and costly, however they are worth doing due to the benefit they bring. Production Forecasting Models are not intended to replace typical workflows but they are intended to help multidisciplinary teams having alternatives during the development and infill drilling planning. The turnaround time and relative low cost to generate seismic production forecasting models make them a great tool to consider in the field development planning.

Seismic production forecasting models are a way to “predict barrels of oil (cumulative production at certain time frame from completion of wells) directly from seismic amplitudes”. Calibration and validation with existing production data is required during the process. It is also constrained and validated with seismic data, well data (logs, tops, etc), core data, microseismic data and engineering data (perforations, stages information, production/well or stage). No data should be ignored in building a model like this.

When an outcome of interest is affected or influenced by more than one attribute the use of techniques like multiattribute statistical analysis is desirable. In the case of production forecasting based on seismic attributes it has been found that the multiattribute statistical analysis technique provides robust results. It has been found that not a single conventional seismic attribute can be related to production however the combination of many of them with other geological and engineering can improve the prediction based on seismic data.

Increasing the seismic resolution of conventional seismic has shown also to be a very powerful tool in the workflow. It helps describe better the heterogeneities of unconventional reservoirs. There seem to be strong lateral and vertical changes on production performance of unconventional reservoirs that can be explained with seismic heterogeneities predicted with increasing the seismic resolution using techniques like sparse layer inversion. In this article, we show the results of a workflow for generating production forecasting models based on properties extracted from high resolution seismic. The models were generated using multivariate statistical analysis.

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/content/papers/10.3997/2214-4609.201702583
2017-11-23
2024-03-28
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References

  1. Zhan, R and Castagna, J.
    2011Sparse layer inversion
    [Google Scholar]
  2. Others, 1999, MVSA
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