survey design identifying data observations to collect and collecting additional data observations related to the formation in some embodiments the performing comprises forming a matrix or loading a matrix or both apparatus and methods of categorizing a subterranean formation including collecting data related to the formation performing an algorithm comprising guided bayesian survey design identifying data observations to use and processing the data observations wherein the observations require less processing time than if no algorithm were performed application_number US 201414162700 A description several techniques have recently arisen to address big data in geoscience including compressive sensing dimension reduction source encoding and optimal experimental design the common goal of these methods is by some means to select and process a smaller data volume while achieving the same or comparable results as though the entire data volume had been used herein we focus on experimental design the theory and practice of designing experiments to maximize the expected information in data observations among the methods noted above optimal design is distinguished because it can be applied a priori before data acquisition to prescribe the observation locations where data are forecast to be most informative for the processing workflow and also a posteriori to select the most informative data from an extant dataset the other methods work only a posteriori and do not optimize the forecasted information in data in other words optimal experimental design is unique because 1 it is an optimization method.