Most unconventional shale reservoirs contain a wide range of in situ hydrocarbons (gas/oil) that are tied to a variety of sources and require extraction methods not commonly used in more conventional settings. As such, new strategies for exploration, characterization and development are required.
To understand and model a source-reservoir formation, both static reservoir modeling and dynamic basin modeling are important. An efficient workflow to combine these methodologies will help obtain a complete view of not only the hydrocarbon evolution history but also the present-day physical state and distribution of these hydrocarbons within the formation itself at the reservoir scale. Here, shale sweet-spot identification is defined based upon the integration of the 3-D static geological model along with the basin dynamic processes acting on rocks and fluids during the development of a sedimentary basin. This workflow contains a variety of conditions and variables, including static petrophysical, geomechanical and geochemical properties from well logs and seismic surveys and dynamic time-based properties such as sedimentation, burial history, erosion, uplift, thermal condition, pressure calculations, diagenesis prediction, etc.
Combining static properties in the earth model with rock and fluid properties from dynamic burial history at the reservoir scale is the heart of this workflow and the key to improving sweet-spot identification.
Combining static properties in the earth model with rock and fluid properties from dynamic burial history at the reservoir scale is the heart of this workflow and the key to improving sweet-spot identification. The proposition is back-stripping the static reservoir model so that the entire history of the reservoir and its constitutive fluids can be recreated. This will assist in validating the structural integrity of the model and provide information about organic matter type, quality, initial and presentday organic matter distribution, and maturity level of the source rock. Maturation simulation will provide information about timing of hydrocarbon generation, the quality and the state of the hydrocarbons (gas, liquids-rich gas and oil). Migration simulation will demonstrate the location of hydrocarbons within the model. Petroleum systems tools allow geologists to quickly evaluate fluid properties within the context of the existing framework using data from available wells. One principle advantage of this approach is the integration of all available geological and geochemical data into a consistent and comprehensive model. This enables a number of assessment capabilities, including risk assessment, evaluation of reservoir potential and optimization of asset development plans.
Integration of geomodeling, basin modeling
Geomodels provide a snapshot of the present-day structural framework of a reservoir along with its orientation and composition and the internal arrangement of the reservoir properties. These models can be either stochastic or deterministic. Figure 1a represents an example of a reservoir model showing the underlying cellular architecture. Figure 1b shows the distribution of porosity in a 3-D geomodel.
The geomodel becomes the input to a basin modeling exercise to validate the distribution of key rock properties and distribute critical fluid properties. It is the addition of the petroleum system analysis and numerical simulation of a basin that improves the sweet-spot definition in unconventional reservoirs. This can create a quality index variable that represents the intersection of optimal petrophysical, geomechanical and geochemical properties and the distribution of the “static” hydrocarbon fluid properties. Additionally, it provides the means by which the reservoir arrived at its current state.
1. Analyze source rock samples. To obtain basic geological and geochemical parameters from source-reservoir formations, source rock samples must first be analyzed using standard methods. This provides information about vitrinite reflectance, total organic carbon (TOC), hydrogen index, oxygen index, kerogen type, rock types and mechanical properties of shale.
2. Perform 1-D basin modeling in several wells/pseudo-wells located in the study area. Calibrated 1-D models will provide information about the history and the present-day state of pressure, maturity, heat flow, erosion, hiatus, tectonic history and rock properties like porosity.
3. Build a high-resolution 3-D model of the reservoir and import results from the 1-D basin model. The geomodel captures the geometry and architecture of the reservoir from seismic and well tops. Petrophysical, geomechanical and geochemical properties are distributed throughout the volume, enabling the identification of the mechanical stratigraphy and associated best characteristics for stimulation and completion. Further, geostatistical methods can be employed to produce a variety of interpolated, simulated and iso-probability maps of key properties such as erosion, organic carbon, hydrogen index and others useful in 3-D basin modeling.
4. Import estimated boundary maps to the 3-D numerical basin model as input data. Simulate and calibrate the model against present-day observed data.
5. Perform uncertainty and sensitivity analysis. Uncertainty and sensitivity analysis is required as it is unlikely that a single unique geological historical scenario exists to explain present-day conditions. A final single best-case scenario can be selected at the end.
6. Import to static reservoir model. Key properties such as effective stress, temperature, maturity, hydrocarbon phase and the other properties can be applied to the reservoir grid and visualized. Further, these properties can be visualized at any historical time from inception to present day.
Geomodeling methods have no capability to describe the means by which a reservoir arrived at its current state nor the predictive condition of the petroleum fluid properties residing within. The quality, quantity and state of hydrocarbons in unconventional reservoirs depend on parameters like the initial geochemistry, maturity level and storage capacity of the source rock, which are better obtained from classic basin modeling. Basin modeling is the key tool to help in the evaluation of initial organic matter distribution, type and quality inside a formation as well as the present day TOC and maturity level of organic matter. These three parameters have a first-order control on the volume of hydrocarbons generated and still retained in the reservoir. Combining classic reservoir characterization with basin modeling at the reservoir scale provides a step forward in modeling unconventional resources.