7.3 Adding geomodeling to volumetric workflows

The traditional volumetric workflow doesn’t involve geomodeling (Figure 1).

Contour maps representing the top horizon, the bottom horizon as well as the faults (if any) are built from the well markers and the seismic interpretation. These maps allow evaluating the bulk rock volume (BRV). The other input parameters are first evaluated on a per well basis, knowing the porosity and So logs as well as the facies description and the elevation of the oil-water contact, if any. NTG is the first parameter being evaluated. Different practitioners follow different approaches; however, we will focus on one hereafter.

In our example, the pay zone is defined as all the sand above the oil-water contact and the net-to-gross is defined as the ratio between the thickness of the pay zone and the total thickness of the geological unit. The average porosity and So values for this well are then computed by arithmetic average from the log values within the pay zone.

At that point, uncertainties are taken into account. Most often, a single set of contour maps exist and only a single BRV can be computed. This is the base-case BRV to which a range of uncertainty is added (for example, +/-5% around the base-case value).

In the meantime, a distribution of average porosity values for the equation is defined from the average porosity values computed at all of the wells. The same is done for the average So and for the net-to-gross.

Lastly, Monte-Carlo sampling techniques are used to run the volumetric equations thousands of times; each run using a set of values BRV, NTG, PORO and So extracted from the respective distributions. The result is a distribution of volumes which give us the range of possible HCPV values based on the input uncertainties.

The use of geomodeling changes the volumetric workflows, even if the general philosophy remains the same (Figure 2).

All the data and the geological knowledge we have are now integrated into a geomodel. At this point uncertainty is not taken into account as a range of values for the BRV, the NTG, the average porosity and the average So. Instead, multiple possible distributions of the facies and the porosity and So logs are built using geostatistical techniques. Then the volume for each realization is computed and together they make the distribution of possible HCPV.

Computing the volume for each realization means computing the volume of oil inside each cell of the 3D grid and then summing up these incremental volumes to get the HCPV volume for the whole 3D grid for the whole reservoir. This illustrates the fundamental difference between the traditional volumetric workflow and the more modern workflow based on geomodeling.

In all cases, the input data are the same: well logs, geophysical data and our overall understanding of the reservoir. On one hand, in the traditional approach, the detailed variation of the logs along the wells is quickly embedded (hidden) inside average values for each well. On other hand, with geomodeling, the detailed well data are used to build a detailed representation of the complex, heterogeneous 3D characteristics of the reservoir.

In a complex reservoir, the traditional approach might have difficulties to properly assess the impact of the 3D heterogeneity of the reservoir on the volume computations. In such cases, building a geomodel is the safest way to go. In simple, homogeneous reservoirs the two approaches will give a similar range of volumes. But considering that building a geomodel for a homogeneous reservoir is a simple, fast task nowadays, it might as well be safer to simply build one for a homogeneous reservoir too instead of relying on the traditional approach.

Table of contents


Chapter 1 - Overview of the Geomodeling Workflow

Chapter 2 - Geostatistics

Chapter 3 - Geologists and Geomodeling

Chapter 4 - Petrophysicists and Geomodeling

Chapter 5 - Geophysicists and Geomodeling

Chapter 6 - Reservoir Engineers and Geomodeling

Chapter 7 - Reserve Engineers and Geomodeling

Chapter 8 - to be published in the summer 2019

To be published mid-March 2018

Chapter 9 - to be published in the summer 2019

To be published mid-March 2018


Follow us

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod.