Abstract: An embodiment of a method for evaluating a schedule for removing a core sample includes generating a model of the core by applying a value of each of the input parameters, one or more of the input parameter values associated with an uncertainty range, and defining a proposed tripping schedule, and performing an evaluation including applying the proposed tripping schedule and a set of expected input parameter values to the model, estimating a core parameter and determining whether the tripping schedule is predicted to be successful by comparing the core parameter to selected core damage criteria. The method also includes iteratively repeating the evaluation, each evaluation being performed using a different combination of input parameter values than any other evaluation, and calculating a probability of success (POS) of the proposed tripping schedule based on a number of evaluations that result in the tripping schedule being predicted to be successful.

Abstract: A method and computer-readable medium for establishing an uncertainty for obtained values of a one-dimensional logging parameter mapped to a three-dimensional volume is disclosed. A relation is formed between the obtained values of the logging parameter and a volumetric parameter of the three-dimensional volume. A set of representative data points is obtained that relates the obtained values of the logging parameter to the volumetric parameter by binning the obtained values. A plurality of regression curves are then determined, wherein each regression curve is obtained by adding a random error to the set of representative data points to obtain a set of randomized data points and performing a regression analysis using the set of randomized data points. The plurality of regression curves are used to establish the uncertainty for the values of the logging parameter in the three-dimensional volume.

Abstract: An embodiment of a method for evaluating a schedule for removing a core sample includes generating a model of the core by applying a value of each of the input parameters, one or more of the input parameter values associated with an uncertainty range, and defining a proposed tripping schedule, and performing an evaluation including applying the proposed tripping schedule and a set of expected input parameter values to the model, estimating a core parameter and determining whether the tripping schedule is predicted to be successful by comparing the core parameter to selected core damage criteria. The method also includes iteratively repeating the evaluation, each evaluation being performed using a different combination of input parameter values than any other evaluation, and calculating a probability of success (POS) of the proposed tripping schedule based on a number of evaluations that result in the tripping schedule being predicted to be successful.

Abstract: An embodiment of a method for constructing a fracture network includes: receiving seismic data collected from a stimulation operation in an earth formation, the seismic data including seismic event data including a first seismic event associated with a first time increment and a second seismic event associated with a subsequent second time increment; and constructing a fracture network model. The model is constructed by: constructing an initial portion of the model based on the first seismic event; and subsequently updating the initial portion of the model based on the second seismic event.

Abstract: A method of estimating flow properties of an earth formation includes: selecting a grid block representing a region of the earth formation, the region including at least one of an area and a volume of the earth formation, the grid block including a plurality of grid cells and having an orientation defined by grid axes; and calculating a fluid flow model of the region. Calculating the model includes: estimating a principal flow direction for each grid cell; adjusting the orientation of the grid block based on the principal flow direction; and calculating fluid flow parameters in each grid cell to generate the fluid flow model.

Abstract: An embodiment of a method for constructing a fracture network includes: receiving seismic data collected from a stimulation operation in an earth formation, the seismic data including seismic event data including a first seismic event associated with a first time increment and a second seismic event associated with a subsequent second time increment; and constructing a fracture network model. The model is constructed by: constructing an initial portion of the model based on the first seismic event; and subsequently updating the initial portion of the model based on the second seismic event.

Abstract: A method of estimating flow properties of an earth formation includes: selecting a grid block representing a region of the earth formation, the region including at least one of an area and a volume of the earth formation, the grid block including a plurality of grid cells and having an orientation defined by grid axes; and calculating a fluid flow model of the region. Calculating the model includes: estimating a principal flow direction for each grid cell; adjusting the orientation of the grid block based on the principal flow direction; and calculating fluid flow parameters in each grid cell to generate the fluid flow model.

Abstract: A method and computer-readable medium for establishing an uncertainty for obtained values of a one-dimensional logging parameter mapped to a three-dimensional volume is disclosed. A relation is formed between the obtained values of the logging parameter and a volumetric parameter of the three-dimensional volume. A set of representative data points is obtained that relates the obtained values of the logging parameter to the volumetric parameter by binning the obtained values. A plurality of regression curves are then determined, wherein each regression curve is obtained by adding a random error to the set of representative data points to obtain a set of randomized data points and performing a regression analysis using the set of randomized data points. The plurality of regression curves are used to establish the uncertainty for the values of the logging parameter in the three-dimensional volume.

Abstract: A method and computer-readable medium for establishing an uncertainty for obtained values of a one-dimensional logging parameter mapped to a three-dimensional volume is disclosed. A relation is formed between the obtained values of the logging parameter and a volumetric parameter of the three-dimensional volume. A set of representative data points is obtained that relates the obtained values of the logging parameter to the volumetric parameter by binning the obtained values. A plurality of regression curves are then determined, wherein each regression curve is obtained by adding a random error to the set of representative data points to obtain a set of randomized data points and performing a regression analysis using the set of randomized data points. The plurality of regression curves are used to establish the uncertainty for the values of the logging parameter in the three-dimensional volume.

Abstract: A method and computer-readable medium for establishing an uncertainty for obtained values of a one-dimensional logging parameter mapped to a three-dimensional volume is disclosed. A relation is formed between the obtained values of the logging parameter and a volumetric parameter of the three-dimensional volume. A set of representative data points is obtained that relates the obtained values of the logging parameter to the volumetric parameter by binning the obtained values. A plurality of regression curves are then determined, wherein each regression curve is obtained by adding a random error to the set of representative data points to obtain a set of randomized data points and performing a regression analysis using the set of randomized data points. The plurality of regression curves are used to establish the uncertainty for the values of the logging parameter in the three-dimensional volume.