Abstract:
This research focused on creating a 3D geological model using well data, to enhance model
accuracy and support the economic development planning of the Xiaermen oilfield. Data
from 40 well were utilized, resulting in a more detailed and accurate model. A sequential
workflow was adopted, beginning with large scale (discrete proprieties) and progressing to
smaller scale proprieties characterized by greater uncertainty, modeled using a
geostatistical method to analyze their distributions across the reservoir.
The Sequential Indicator Simulator and Sequential Gaussian Simulation Algorithms were
used under stochastic model to distribute reservoir proprieties effectively. This study
underscores the importance of well-data-driven 3D Geological Modelling in Reservoir
Characterization, highlighting the used methodology in this domain.
By integrating a diverse data source, this study identified critical geological feature such
as facies distributions, porosity variations and fluid saturations enabling robust decision
making processes. Incorporating well data with seismic information, allowed geoscientists
to correlate seismic attributes with reservoir properties, significantly improving the
accuracy of the resulting geological models. This integration also provided a more precise
understanding of the reservoir's structural framework, fault systems, and stratigraphic
variations, essential for optimized reservoir management and development.
