G01V11/00

METHOD FOR IMPROVING SURVEY MEASUREMENT DENSITY ALONG A BOREHOLE
20170284183 · 2017-10-05 ·

A method may include providing a drill string including a measurement tool. The drill string may be positioned in a wellbore. The method may include taking a measurement with the measurement tool at a first location. The method may include coupling a pipe stand including a first selected number of tubular segments to the drill string, the first selected number being two or more. The method may include lowering or advancing the drill string into the wellbore the length of the pipe stand. The method may include taking a measurement with the measurement tool at a second location. The method may include raising the drill string the length of a tubular segment. The method may include removing a second selected number of tubular segments from the drill string, the second selected number different from the first selected number. The method may include taking a measurement with the measurement tool at a third location. The method may include raising the drill string the length of the first selected number of tubular segments. The method may include removing the first selected number of tubular segments. The method may include taking a measurement with the measurement tool at a fourth location.

EVALUATING ANISOTROPIC EFFECTIVE PERMEABILITY IN ROCK FORMATIONS HAVING NATURAL FRACTURE NETWORKS
20220050224 · 2022-02-17 ·

A fracture simulation system is provided to determine anisotropic effective permeability of rock formations having natural fractures therein.

Visual interface for identifying layers within a subterranean formation

The present disclosure relates to a visual interface for identifying layers within a subterranean formation. One example method includes identifying one or more sets of data associated with a subterranean formation; computing, by operation of one or more processors, a working line based on the one or more sets of data, the working line representing a numerical average of the one or more sets of data; presenting the working line and the one or more sets of data in a common plot in a visual interface; identifying one or more layer boundaries for one or more of the layers of the subterranean formation; and generating layer data based on the one or more identified layer boundaries and the working line.

Visual interface for identifying layers within a subterranean formation

The present disclosure relates to a visual interface for identifying layers within a subterranean formation. One example method includes identifying one or more sets of data associated with a subterranean formation; computing, by operation of one or more processors, a working line based on the one or more sets of data, the working line representing a numerical average of the one or more sets of data; presenting the working line and the one or more sets of data in a common plot in a visual interface; identifying one or more layer boundaries for one or more of the layers of the subterranean formation; and generating layer data based on the one or more identified layer boundaries and the working line.

Method and system for generating a geoid via three computation spaces and airborne-acquired gravity data
09778360 · 2017-10-03 · ·

Airborne gravity measurements may be added to the collection of airborne LiDAR so that it may be used to produce a digital elevation model (DEM), which may be used along with gravity data to produce an improved geoid, which may be used to produce an improved DEM based on the improved orthometric heights. A computing device may be configured to receive airborne navigation, gravity and LiDAR data, generate position information based on the navigation data, generate gravity field information based on the gravity data and the position information, generate orthometric height information based on the LiDAR data and the position information, and generate a geoid based on the gravity field and orthometric height information. The computing device may also generate a geoid model based on the gravity field and an existing DEM, and generate the orthometric height information based on the LiDAR data, position information, and geoid model.

DISTRIBUTED SENSING SYSTEM EMPLOYING A FILM ADHESIVE

A sensing apparatus includes a sheath, a central member disposed in the sheath, at least one optical fiber disposed with the central member, and a film adhesive disposed between the central member and the sheath, the film adhesive provided in one or more sheets or strips and disposed in one or more layers between the central member and the sheath, and the film adhesive attached to the sheath.

Simulated Core Sample Estimated From Composite Borehole Measurement

Methods, systems, and devices for evaluating an earth formation intersected by a borehole using information from standard resolution measurements. Methods include generating an image representative of the formation over an interval of borehole depth, the image having a second resolution greater than the first resolution. Generating the image may be carried out by identifying layers corresponding to lithotype facies within the interval, the layers defined by boundaries having boundary locations along the borehole; and using a unified characterization of the formation within the interval determined from the standard resolution measurements and the boundary locations within the interval to solve for a value for the formation parameter corresponding to each layer consistent with the unified characterization of the interval. The unified characterization may be an average value for the formation parameter within the interval.

METHOD OF CHARACTERISING A SUBSURFACE VOLUME
20170248718 · 2017-08-31 · ·

Disclosed is a method of characterising a subsurface volume. The method comprises: extracting a geobody from seismic data arranged within a discretised volume comprising a plurality of cells, the geobody comprising a subset of the plurality of cells, each cell of the subset having one or more properties indicative of a particular fluid phase. The extraction of the geobody comprises: determining a propagation probability value for each cell indicative of the probability that a front will propagate through the cell; beginning from a source within the discretised volume, using the propagation probability value to calculate a travel-time for each cell, the travel time describing the time the front takes to travel from the source point to the cell; and using the traveltimes to extract the geobody from the seismic data.

METHOD FOR PREDICTING CASED WELLBORE CHARACTERISTICS USING MACHINE LEARNING
20220043179 · 2022-02-10 · ·

A method for well integrity assessment using machine-trained prediction of physical characteristics related to well integrity across a depth interval of a cased wellbore having one or more casing strings. The method includes collecting scattered X-ray signals from a plurality of X-ray detectors arranged within a well logging tool, learning trained weights to predict wellbore characteristics from the scattered X-ray signals, collecting further scattered X-ray signals from the X-ray detectors, using the trained weights to quantitatively predict the wellbore characteristics from the further X-ray signals, and using the predicted wellbore characteristics to assess well integrity.

METHODS OF GENERATION OF FRACTURE DENSITY MAPS FROM SEISMIC DATA
20170248719 · 2017-08-31 ·

A method is herein presented to statistically combine multiple seismic attributes for generating a map of the spatial density of fractures. According to an embodiment a first step involves interpreting the formation of interest in 3D seismic volume first to create its time structure map. The second step is creating depth structure of the formation of interest from its time structure map. In this application geostatistical methods have been used for depth conversional, although other methods could be used instead. The third step is extraction of a number of attributes, such as phase, frequency and amplitudes, from the time structure map. The next step is to project the fracture density onto the top of the target formation. The final step is to combine these attributes using a statistical method known as Multi-variant non-linear regression to predict fracture density.