Unconventional resource plays have come front and center in the exploration and development arena, particularly in North America. Effective modeling efforts of these resources are struggling to keep pace with exploitation, principally due to lack of understanding shales and the need to minimize costs. Currently, the industry is in a state of trial and error, with only immature research results available to help improve defining the physical characteristics of source/reservoir sweet spots and the appropriate methods to stimulate them. Traditionally, reservoir geomodeling has focused on present-day descriptions of static rock properties in the subsurface in a localized area but has no capability to describe the means by which the reservoir arrived at this current state along with the distribution of fluids. The state of petroleum is usually determined in a regional basin model, which simulates, through time, a variety of conditions and variables with all of the processes acting on rocks and fluids post-deposition.

Traditional workflows and methods for identifying good and poor reservoir quality in shales have not been successful, principally due to our lack of understanding shales and the difficulty of remotely identifying their quality with current tools (Figure 1). The emphasis has been to reduce costs through “factory drilling,” a method involving a succession of laterally drilled wells from a common pad and a common completion recipe.

FIGURE 1. Of the shale literature published in the last 35 years, half of what the industry now knows about shales has been published in the last three years. (Source: Landmark)

Because of the relatively short time frame within the basin history in which the shale resource was deposited, a calibrated dynamic version of the regional basin model at the scale of a reservoir is feasible. The advantage of doing so is to recreate its entire history and its constitutive fluids to determine when the hydrocarbons were generated, where they currently reside, their quality and their current phase (gas, liquid-rich, oil).

Static earth model

The contribution of the static earth model is to provide a 3-D representation of the current distribution of petrophysical and mechanical properties in the context of the present-day structural framework for a variety of downstream operations such as well planning and flow simulation (Yarus and Chambers, 2006).

Figure 2 represents a sample earth model showing the distribution of matrix porosity calibrated to seismic acoustic impedance, total organic carbon (TOC), brittleness and the structural framework in which it was built. Two directions of natural fracturing are present in portions of the model where rocks are most brittle.

Dynamic basin model

Basin modeling concerns the simulation of sedimentation, burial, erosion, uplift, thermal calculation, pressure calculations, diagenesis prediction, etc.—all of the processes acting on rocks and fluids during the development of a sedimentary basin. The modeling process is generally applied to entire basins or large portions of them.

Typical reservoir modeling concerns the present-day description of the rock and fluid properties in the subsurface in a highly localized area, with no means to calculate or describe the events by which the reservoir arrived at this state. Here we describe a workflow for performing “basin” modeling at the reservoir scale, providing a link between present-day and the historical process that acted on the rocks and fluids.

FIGURE 2. This 3-D geocellular earth model shows the framework and distribution of matrix porosity calibrated to acoustic impedance, porosity and TOC. (Source: Landmark)

Model building, burial history

In parallel to a static geocellular earth model, a basin modeling study is performed over the corresponding area. If the area is relatively small such that thermal, pressure and other effects are more or less uniform over the study area, a one-dimensional basin model might be sufficient.

The primary objective of the basin modeling study is to determine the burial history of the reservoir, specifically, its pressure (stress) and temperature histories.

The burial history information from the basin study can be applied to the reservoir model. The reservoir structural model is assumed to be correct, and a temperature gradient and overburden is determined. The objective of this step is to provide both rock and fluid properties through time and ideally arrive at a solution that calibrates to present-day conditions.

The effective stress, temperature and other properties derived from the basin model are applied to the reservoir grid. The basin model provides these properties for a number of discrete time points in the past. The output of this process is the through-time representation of the rock properties on the reservoir at the resolution of the original earth model. At this point, geomechanical and other production evaluation-oriented rock properties can also be calculated from the same process.

FIGURE 3. This image shows the burial history from the basin model. (Source: Landmark)

Deriving fluid properties

The distributions of petroleum fluid properties are arguably a more important attribute because they address the fundamental economic basis of the oil and gas industry. In the same way that each element in the model was assigned a lithology ID that led to the calculation of rock properties, a source type ID is also assigned to calculate source fluid properties, a source property calculator that includes in situ fluid and rock-fluid reactions that occur within the source through time. By applying the burial history (Figure 3) to the model, the sediment and source maturities of expelled and adsorbed masses can be calculated. The masses of the fluid components can then be combined with the historical pressure and temperature information to provide pressure-, volume- and temperature-based fluid properties. These would include phase state fluid densities and fluid viscosities.

Calibration and sweet spot identification

The end results of this workflow are a suite of both rock and fluid properties described at the resolution and scale of the original reservoir model. Combined, this can provide a comprehensive set of properties to not only prepare the static reservoir model for dynamic simulation but also for well planning. Additionally, sweet spots can be determined based on a combined set of rock and fluid properties, further contributing to drilling and completions strategies.

Better development

While shale resources have the capacity to dramatically change the balance of energy independence globally, identifying precisely how they work and how they can best be commercially exploited is still unclear. The distribution of static properties in an earth model integrated with rock and fluid properties from dynamic burial history can significantly improve sweet spot identification. As part of a complete workflow from static modeling to dynamic modeling through production, an understanding of the through-time history of the reservoir will provide a more solid foundation upon which to build a knowledge base for better drilling programs and economic forecasting.

Comments