Abstract: Methods and systems for trend modeling of subsurface properties are disclosed. One method includes defining a stratigraphic grid of a subsurface volume, the stratigraphic grid including a plurality of columns and a plurality of layers. The method further includes determining, for each layer or column, an initial average property value based at least in part on well data in the subsurface volume and a confidence interval around that initial average property value defining a range of likely values for a target average property value. The method also includes receiving one or more user-defined edits to the initial average property value in one or more of the layers or columns, the one or more edits resulting in the modeled target average property value, and determining whether the modeled target average property value falls within the confidence interval.

Abstract: A system and a method, implemented on a computer, for calculating property distribution uncertainty of spatially correlated petrophysical data. The method includes inputting, into the computer, a sample petrophysical data comprising correlated data; applying, using the computer, a variogram to the sample petrophysical data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample petrophysical data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating data distributions for each of the obtained plurality of bootstrap data sets; ranking the data distributions by using a selected statistical parameter to obtain ranked data distributions; and characterizing the uncertainty based on the ranked data distributions.

Abstract: A method, implemented on a computer, for calculating vertical trend curve uncertainty of spatially correlated reservoir data. The method includes inputting, into the computer, a sample reservoir data comprising correlated data; applying, using the computer, a variogram to the sample reservoir data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample reservoir data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating vertical trend curves for each of the obtained plurality of bootstrap data sets, ranking the vertical trend curves by using a selected statistical parameter to obtain ranked vertical trend curves, and characterizing the uncertainty based on the ranked vertical trend curves.

Abstract: A computer system and a hybrid method for combining multipoint statistic and object-based methods include creating a multi-point statistics (MPS) model using a MPS method that satisfies conditioning data and constraints in which the multi-point statistics are derived from a training image created using training-image generation parameters; generating one or more object-shape templates and depositional or structural coordinates of each facies type using the generation parameters; positioning the one or more generated templates within the MPS model such that the one or more generated templates maximally correlate to the MPS model; assigning to each of the one or more positioned templates a unique event; providing depositional or structural coordinates to each cell associated with a given event number; and modeling properties using the coordinates to capture geological trends within each template.

Abstract: A computer system and a hybrid method for combining multipoint statistic and object-based methods include creating a multi-point statistics (MPS) model using a MPS method that satisfies conditioning data and constraints, the multi-point statistics being derived from a training image created using training-image generation parameters; generating one or more object-shape templates and depositional coordinates of each facies type using the parameters; positioning the templates within the MPS model such that the templates maximally correlate to the MPS model; assigning to each of the positioned templates a unique event; determining which cells are available for editing; and assigning the cells that are available for editing to facies if the cells are contained by a facies template positioned within the MPS model at its optimally correlating location.

Abstract: A computer system and a hybrid method for combining multipoint statistic and object-based methods include creating a multi-point statistics (MPS) model using a MPS method that satisfies conditioning data and constraints, the multi-point statistics being derived from a training image created using training-image generation parameters; generating one or more object-shape templates and depositional coordinates of each facies type using the parameters; positioning the templates within the MPS model such that the templates maximally correlate to the MPS model; assigning to each of the positioned templates a unique event; determining which cells are available for editing; and assigning the cells that are available for editing to facies if the cells are contained by a facies template positioned within the MPS model at its optimally correlating location.

Abstract: A computer system and a hybrid method for combining multipoint statistic and object-based methods include creating a multi-point statistics (MPS) model using a MPS method that satisfies conditioning data and constraints in which the multi-point statistics are derived from a training image created using training-image generation parameters; generating one or more object-shape templates and depositional or structural coordinates of each facies type using the generation parameters; positioning the one or more generated templates within the MPS model such that the one or more generated templates maximally correlate to the MPS model; assigning to each of the one or more positioned templates a unique event; providing depositional or structural coordinates to each cell associated with a given event number; and modeling properties using the coordinates to capture geological trends within each template.

Abstract: A method of automatically interpreting well log data indicative of physical attributes of a portion of a subterranean formation which include some portion of samples with known facies classification to be used as training data, dividing the training data into two subsets, a calibration set and a cross-validation set, using an automated supervised learning facies identification method to determine a preliminary identification of facies in the subterranean formation based on the calibration set, calculating a confusion matrix for the supervised learning facies identification method by comparing predicted and observed facies for the cross-validation set, calculating a facies transition matrix characterizing changes between contiguous facies, and using the preliminary identification, the facies transition matrix, and the confusion matrix, iteratively calculating updated facies identifications.

Abstract: A system and method, implemented on a computer, for determining the uncertainty of soft-data debiasing of property distributions of spatially correlated reservoir data are provided. The method includes inputting, into the computer, soft-data at a plurality of spatial locations on a grid and hard-data at a plurality of location along well paths that intersect the grid. Each location of the hard-data is collocated with soft-data values of one or more types.

Abstract: A computer system and a computer-implemented method for calibrating a reservoir characteristic including a permeability of a rock formation. The method includes inputting a measured product KH of a measured permeability K and a flowing zone thickness H over a plurality of corresponding zones in one or more wells and inputting porosity logs for each measured product KH in each of the plurality of zones obtained from the one or more wells. The method further includes reading a porosity-permeability cloud of data points; calculating, for each zone, a predicted product KH from the porosity log using the porosity-permeability cloud of data points; determining one or more weighting coefficients between the predicted KH and the measured KH corresponding to each zone; and calibrating the measured permeability corresponding to each zone using the one or more weighting coefficients.

Abstract: A method of modeling porosity and permeability in a subsurface region includes modeling a sparse data set as a mixture of Gaussian distributions, each with a cluster center in permeability-porosity space using permeability-porosity covariance. A number and location of cluster centers as well as covariances and probabilities of each cluster are derived using an interative maximum-likelihood algorithm.

Abstract: A method, implemented on a computer, for calculating vertical trend curve uncertainty of spatially correlated reservoir data. The method includes inputting, into the computer, a sample reservoir data comprising correlated data; applying, using the computer, a variogram to the sample reservoir data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample reservoir data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating vertical trend curves for each of the obtained plurality of bootstrap data sets, ranking the vertical trend curves by using a selected statistical parameter to obtain ranked vertical trend curves, and characterizing the uncertainty based on the ranked vertical trend curves.

Abstract: A system and a method, implemented on a computer, for calculating property distribution uncertainty of spatially correlated petrophysical data. The method includes inputting, into the computer, a sample petrophysical data comprising correlated data; applying, using the computer, a variogram to the sample petrophysical data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample petrophysical data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating data distributions for each of the obtained plurality of bootstrap data sets; ranking the data distributions by using a selected statistical parameter to obtain ranked data distributions; and characterizing the uncertainty based on the ranked data distributions.

Abstract: A method of locating resources in a reservoir that includes at least one injection well and at least one production well includes mapping a modeled permeability characteristic of structures making up the reservoir, computing, based on the modeled permeability characteristic, an indicator of flow velocity for streamlines from each production well, computing, based on the modeled permeability characteristic, an indicator of flow velocity for streamlines from each injection well, and combining the indicators of flow velocity from each production and injection well to characterize a sweep efficiency of the reservoir system.

Abstract: A method is provided that utilizes independent data spatial bootstrap to quantitatively derive P10, P50 and P90 reservoir property logs and zonal averages. The method utilizes at least a “baseline” dataset that is assumed to be correct, and determines the distribution of possible input parameter values that provide the most optimal solution to fit the log analysis to the core data. In one embodiment, independent data spatial bootstrap method can be applied to determine the uncertainty of porosity and saturation.

Abstract: A method of normalizing well log data relating to geology of a subsurface region includes identifying a pair of markers defining a zone on each well log, determining a statistic for a property within the zone for each well log, fitting a smooth function to the statistics to create a first-iteration trend surface, determining, for each statistic, a deviation from the trend surface and eliminating those statistics that deviate from the trend surface by greater than a threshold value, fitting a smooth function to the remaining statistics to create a second-iteration trend surface, normalizing the property for each well log based on the second-iteration trend surface, and analyzing the normalized properties to determine the geology of the subsurface region.

Abstract: A method of automatically correlating well logs includes selecting well loops from the well logs and creating a set of possible marker positions for each well log in each well loop. From the possible marker positions, alternate marker sets are iteratively selected. A well tie error on each loop is calculated for each selected marker set, summed over all loops and minimized.

Abstract: A method of normalizing well log data relating to geology of a subsurface region includes identifying a pair of markers defining a zone on each well log, determining a statistic for a property within the zone for each well log, fitting a smooth function to the statistics to create a first-iteration trend surface, determining, for each statistic, a deviation from the trend surface and eliminating those statistics that deviate from the trend surface by greater than a threshold value, fitting a smooth function to the remaining statistics to create a second-iteration trend surface, normalizing the property for each well log based on the second-iteration trend surface, and analyzing the normalized properties to determine the geology of the subsurface region.

Abstract: A method of locating resources in a reservoir that includes at least one injection well and at least one production well includes mapping a modeled permeability characteristic of structures making up the reservoir, computing, based on the modeled permeability characteristic, an indicator of flow velocity for streamlines from each production well, computing, based on the modeled permeability characteristic, an indicator of flow velocity for streamlines from each injection well, and combining the indicators of flow velocity from each production and injection well to characterize a sweep efficiency of the reservoir system.

Abstract: A method of automatically correlating well logs includes selecting well loops from the well logs and creating a set of possible marker positions for each well log in each well loop. From the possible marker positions, alternate marker sets are iteratively selected. A well tie error on each loop is calculated for each selected marker set, summed over all loops and minimized.