What are the common mistakes in petrophysical modeling of carbonate reservoirs?

1 Mistake 1: Ignoring the impact of diagenesis

Diagenesis is the process of physical and chemical alteration of carbonate rocks after deposition. It can affect the pore structure, mineral composition, and fluid distribution of the reservoir. For example, dolomitization can increase porosity and permeability, while cementation can reduce them. Therefore, ignoring the impact of diagenesis can result in erroneous interpretation of well logs and seismic data, as well as misleading calculation of volumetric and recovery factors. To avoid this mistake, it is important to identify and characterize the diagenetic features and processes that affect the reservoir, and incorporate them into the petrophysical model.

2 Mistake 2: Using inappropriate rock typing methods

Rock typing is the process of grouping reservoir rocks into discrete classes based on their petrophysical characteristics, such as porosity, permeability, pore geometry, and fluid saturation. Rock typing is essential for petrophysical modeling, as it allows to assign representative properties and functions to each rock type. However, using inappropriate rock typing methods can lead to oversimplification or overcomplication of the reservoir heterogeneity, and affect the quality and reliability of the model. To avoid this mistake, it is important to use rock typing methods that are suitable for carbonate reservoirs, such as those based on capillary pressure, NMR, or image logs, and to validate them with core and dynamic data.

3 Mistake 3: Neglecting the effects of fractures

Fractures are ubiquitous in carbonate reservoirs, and can have a significant impact on the fluid flow and storage capacity of the reservoir. Fractures can enhance or reduce the effective porosity and permeability of the reservoir, depending on their orientation, density, aperture, connectivity, and filling. Therefore, neglecting the effects of fractures can lead to underestimation or overestimation of the reservoir productivity and reserves. To avoid this mistake, it is important to detect and quantify the fractures from well logs, core, and seismic data, and to incorporate them into the petrophysical model as discrete or dual porosity systems.

4 Mistake 4: Applying incorrect saturation models

Saturation models are mathematical expressions that relate the fluid saturation to the capillary pressure and the relative permeability of the reservoir. Saturation models are crucial for petrophysical modeling, as they determine the fluid distribution and mobility in the reservoir. However, applying incorrect saturation models can lead to unrealistic or inconsistent results, and affect the accuracy and sensitivity of the model. To avoid this mistake, it is important to use saturation models that are appropriate for carbonate reservoirs, such as those based on Leverett J-function, Brooks-Corey, or Thomeer models, and to calibrate them with core and well test data.

6 Mistake 6: Not validating and verifying the model

Validation and verification are essential steps in petrophysical modeling, as they ensure that the model is consistent with the available data and the underlying assumptions. Validation is the process of comparing the model outputs with the observed data, such as well logs, core, seismic, and production data. Verification is the process of checking the model inputs, parameters, and functions for errors and uncertainties. Not validating and verifying the model can lead to unreliable or erroneous predictions and decisions, and compromise the value and credibility of the model. To avoid this mistake, it is important to perform validation and verification at every stage of the modeling process, and to document and communicate the results and limitations of the model.