
FAQs
Frequently asked questions
Petrophysical applications commercially available (like Geolog®, Techlog®, PowerLog®, LESA®, etc.) have a multimineral analysis module that requires the mineral and fluids coefficients (also called end-points) to be well known. When performing mutlimineral analysis the petrophysicist needs to input the values of each coefficient or use the default values provided by the software. After modeling synthetic logs, the petrophysicist then modifies the coefficients until he/she is satisfied with the agreement between observed and modeled logs. For simple lithologies or mineral compositions this process is fairly straight forward. As we develop reservoirs with more complex lithologies, however, our uncertainty about the values of the coefficients increases. In these instances, the petrophysicist needs to adjust the coefficients in a trial-and-error fashion until a satisfactory result is achieved. Since the coefficients may be dependent on one another, a change in one coefficient typically requires changes in other coefficients. iMineralysis™ automates this trial-and-error process and produces resuts where the coefficients are consistent among themselves.
iMineralysisâ„¢ allows you to set the initial set of coefficients and a range of a suspected uncertainty. Then, iMineralysis not only then performs the estimation of mineral fractions but also intelligently tests hundreds of combinations within the specified ranges by using a genetic algorithm based optimization. Basically, it performs the multimineral analysis for hundreds of possible cases in seconds! With iMineralysisâ„¢ the petrophysicist can achieve a solution that can be impossible or too time consuming with any other commercial tool as it can require too many tests.
Besides automating the trial-and-error process in the multimineral analysis, iMineralysisâ„¢ provides diagnostics that can help determine the non-uniqueness of the solutions. Using these diagnostic tools, the user can identify which mineral constants need additional constraints in order to reduce the non-uniqueness. This capability is not available in other commercially available applications of multimineral analysis.
The values of the mineral constants that are typically used as input for multimineral analysis are related to pure minerals (quartz, calcite, dolomite, etc.). In reality, however, the rocks are formed by a complex mix of minerals, even in areas that we consider to be mineralogically simple. For instance, in intervals where only sand and clay are present, the petrophysicist tends to select quartz and illite as the basic minerals that make the rock even though in clastic environments we know that the composition can be more complex. Quartz is often accompanied by feldspars, and clay usually comes in a mix of illite, smectite, and mica. Those individual minerals are very difficult, if not impossible, to solve by using logs only and therefore, the petrophysicist usually solves for the mixes that results in sand and clay. Since the properties available in the literature are for the pure minerals but it is not possible to for solve for them individually, the petrophysicist needs to vary the initial constants associated to each mix until he/she achieves an optimal solution. iMineralysisâ„¢ helps the petrophysicist to obtain this solution by intelligently testing hundreds of possibilities.
By estimating the matrix of coefficients using wells from different areas and different intervals, you can estimate spatial variations in water resistivity, kerogen maturity, and clay composition.
You can also:
Identify by-passed-pay
Identify kerogen grain-density trends vs. thermal maturity
Independently quantify variable Rw trends
Create effective hydrocarbon pore volume ranges
Perform uncertainty analysis for petrophysics constraints in reservoir models
Create lithology-based geomechanics-constraints
The constituents are the minerals and fluids of the system you are trying to solve for. When you select the number of constituents it includes both minerals and fluids. The typical system to use has a minimum of 2 minerals and 2 fluids, but depending on the application you can also have only one fluid (water, for instance), or more minerals depending on the number of logs available and the complexity of the mineral composition.
No. The estimation of the mineral coefficients is a highy non-unique and nonlinear problem that requires as much information and constraints as you are able to provide. These constraints may come in the form of expected mineralogy (from core descriptions), initial values from the literature, expected ranges of variations for each coefficient and internal relations between coefficients. Once you provide the initial information, iMineralysisâ„¢ can help you to refine it while honoring your input well logs. iMineralysisâ„¢ also provides a few pre-build models for different geological scenarios that can be modified by the user to meet his/her specific needs.
The simultaneous inversion of all fractions (volumes) of components is based on the assumption that the measured logs are a linear combination of such fractions and the tool responses for each component. However, the resistivity log is not linearly related to the volume of the components of the system. In this case, the resistivity tool can be linearized by using a "pseudo-conductivity" instead of the resistivity. The Cx corresponds to one over resistivity elevated to the root of the "m" exponent (1/Rt)^(1/m) of the Archie equation. In iMineralysisâ„¢, the water saturation model assumed is a modified Archie equation with m=n.
U is the volumetric photoelectric factor. The litho-density log tool measures the Photoelectric Factor (PE). The simultaneous inversion of all logs is based in the assumption that the log responses of each mineral/fluid are linearly related with the volume of each component. Although the PE tool doesn’t relate linearly with the volume of the components of the system, the photoelectric factor U estimated as PE*RHOB does.
