The Challenges Brought by Oilfield Development Methods to Geological Modeling: Big Data Paradox and Modeling Strategies Based on Horizontal Wells Data

Abstract

The challenges brought by oilfield development methods to geological modeling:Big data paradox and modeling strategies based on horizontal wells data

Horizontal wells have been extensively applied to the development of old oilfields, low- permeability oil and gas fields and heavy oil reservoirs. Different from previous modeling based on vertical well data, the application of horizontal well data has a great effect on the geological modeling results of reservoirs. The horizontal section of a horizontal well extends longer, so the sand bodies and the corresponding physical property parameters are char-acterized more accurately, and the uncertainty of interwell prediction is reduced. Due to the particular well arrangement mode of horizontal wells, however, a large amount of data is collected in a specific direction, leading to greater effect on data statistical analysis and variogram calculation, and consequently, the paradox occurs in the subsequent sedimentary facies and physical property model. This paper took MPE3 oil field in Orinoco heavy oil belt as an example to analyze the differences of data distribution and variogram between vertical and horizontal wells.Data of horizontal wells are not only in huge numbers but also with obvious orientation and high sandstone-encountered rate due to the manual controlling the well trajectory. The study show that big data of horizontal wells result in unperfect variogram analysis which is not in accordance with geological study because the horizontal wells in the study area are mainly perpendicular to the direction of the river channels. Furthermore, it will cause mistakes about the predictions of sedimentary microfacies, reservoir property and probabilistic reserves. In order to avoid this kind of big data paradox generated from the horizontal well information directly applied to geological modeling, we put forward a corresponding strategy in reservoir modeling. When modeling, firstly, the analysis and calculation of channel distribution variograms were obtained with vertical wells data. And then the distribution of river channels was predicted under the control of the sedimentary facies patterns and seismic data. After that, the vertical and horizontal wells were integrated to do the data analysis of shally interlayer variograms and the corresponding reservoir lithofacies models were constructed. Finally, reservoir property models were generated and the geological reserves were calculated through well groups one by one. This kind of reservoir modeling method does not only reflect the distribution reality of underground geo-bodies, but also improve the accuracy of the prediction of inter-well sand bodies and enhance the geo-model’s reliability.

AAPG Datapages/Search and Discovery Article #90350 © 2019 AAPG Annual Convention and Exhibition, San Antonio, Texas, May 19-22, 2019