Identification of underground hydrocarbon bearing formations, and extraction of hydrocarbons from such formations, generates a significant amount of data. In particular, each borehole drilled into a hydrocarbon bearing formation may be logged by a host of different logging tools, both during drilling, and after the borehole is cased. Generally speaking, the data and information gathered about the earth formations surrounding the borehole are stored, and in many cases the data and information are used in the planning and drilling of other boreholes in relatively close proximity.
Consider a situation where multiple boreholes have been previously drilled into a hydrocarbon bearing formation, and multiple logs have been taken within each borehole. When planning the next borehole to be drilled, the formation properties along the proposed borehole path will be estimated using the logs from all the multiple previously drilled boreholes. The data resolution for each log may on the order of six inches (i.e., a datum in the log representing the value of the formation parameter measured for every six inches), and thus the number of data points to consider when estimating the formation properties along the proposed borehole path is enormous. For this reason, in the related art updating of models or predictions of formation parameters along a proposed borehole path cannot be accomplished in real time with the drilling along the proposed borehole path.
Thus, any advance which results in an ability to calculate updates of predicted formation parameters in less time or with less computing power, would provide a competitive advantage.