# US 11,442,188 B2 · Dip detection in logging image processing > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,442,188 B2 - Document ID: US11442188B2 - Status: Granted - Kind: B2 - Application number: 16/488,676 - Filed: 2019-03-28 - Published: 2021-11-18 - Granted: 2022-09-13 - Earliest claimed: 2018-03-30 - Assignees: Halliburton Energy Services, Inc. - Applicants: Halliburton Energy Services, Inc. - Inventors: Nam Nguyen; David Orlando Torres; Gary Wayne Kainer - Web page: https://patentgrep.com/patent/US11442188B2 ## CPC - G01V 1/345: {Visualisation of seismic data or attributes, e.g. in 3D cubes} - G05B 19/02: electric - E21B 47/026: of penetrated ground layers - G01V 3/24: using AC - G06T 3/4007: based on interpolation, e.g. bilinear interpolation (image demosaicing G06T3/4015; edge-driven or edge-based scaling G06T3/403) - G01V 2210/74: Visualisation of seismic data - G05B 2219/45129: Boring, drilling - G06F 2218/02: Preprocessing - G06F 2218/14: by matching peak patterns - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method for imaging a downhole formation. The method includes combining the captured images to generate a partial image of the formation, wherein the partial image includes captured images separated by gaps representing portions of the formation not captured with sensors what were disposed downhole. The method includes locating dips in the formation within the partial image and interpolating the partial image using the located dips within the partial image. ## Claims ### Claim 1 A method for imaging a downhole formation, the method comprising: combining captured images to generate a partial image of a formation, wherein the partial image includes the captured images acquired from at least one sensor disposed on a tool within the formation, the captured images separated by gaps representing portions of the formation not captured by the at least one sensor; locating dips in the formation within the partial image, to provide located dips, wherein locating dips in the formation within the partial image comprises identifying peak sections in the partial image based on a differential of each vertical line and portions of the partial image along a depth; and interpolating the partial image, using the located dips within the partial image, to construct image data for the gaps of the partial image to create a full interpolated image of the formation. ### Claim 2 (depends on 1) The method of claim 1, wherein interpolating the partial image comprises using texture extraction techniques. ### Claim 3 (depends on 1) The method of claim 1, wherein locating dips in the formation within the partial image comprises using median filtering to identify the peak sections. ### Claim 4 (depends on 1) The method of claim 1, wherein locating dips in the formation within the partial image comprises: dip-fitting peak sections across the captured images by using linear least-squares fitting to define potential dips; and ranking the potential dips based on any one or combination of fitting distance error, smoothness of the dips, and dip frequency deviation. ### Claim 5 (depends on 1) The method of claim 1, wherein locating dips in the formation within the partial image comprises incorporating a misalignment coefficient. ### Claim 6 (depends on 1) The method of claim 1, wherein locating dips in the formation within the partial image comprises combining peak sections that are connected to form a peak area for each portion of the partial image detected by the at least one sensor. ### Claim 7 (depends on 1) The method of claim 1, wherein locating dips in the formation within the partial image comprises performing a dip-fitting over a peak area using a sliding window along a depth axis to locate the dip. ### Claim 8 A system for determining a dip of a formation, the system comprising: a logging tool to be positioned in a borehole within the formation, the logging tool comprising at least one sensor disposed on one or more pads, wherein the at least one sensor is to detect signals representing portions of captured images of the formation; a processor; and a machine-readable medium having program code executable by the processor to cause the processor to, generate a combined image of the formation that includes the captured images; and detect a dip in the formation within the combined image, wherein the program code to detect the dip also includes program code to cause the processor to, determine a differential of vertical lines and portions of the combined image along a depth; identify peak sections in the combined image based on the differential of each vertical line; combine the peak sections that are connected to form a peak area for each portion of the combined image detected by the at least one sensor; and perform a dip-fitting over the peak area using a sliding window along a depth axis to locate the dip. ### Claim 9 (depends on 8) The system of claim 8, wherein the program code to identify the peak sections in the combined image comprises program code to cause the processor to apply median filtering to identify the peak sections. ### Claim 10 (depends on 8) The system of claim 8, wherein the program code to perform the dip-fitting over the peak area comprises program code to cause the processor to: dip-fit the peak area across the captured images by using linear least-squares fitting; and rank potential dips based on fitting distance error, smoothness of the dips, or dip frequency deviation. ### Claim 11 (depends on 10) The system of claim 10, wherein a total number of the potential dips that are ranked is reduced by decreasing the number of peak areas used in the linear least-squares fitting. ### Claim 12 (depends on 8) The system of claim 8, wherein the program code to perform the dip-fitting over the peak area comprises program code to cause the processor to incorporate a misalignment coefficient. ### Claim 13 One or more non-transitory machine-readable media comprising instructions executable by a processor to cause the processor to: combine captured images to generate a partial image of a formation, wherein the partial image includes the captured images acquired from at least one sensor disposed on a tool within the formation, the captured images separated by gaps representing portions of the formation not captured by the at least one sensor; locate dips in the formation within the partial image, to provide located dips, wherein the location of dips in the formation within the partial image comprises an identification of peak sections in the partial image based on a differential of each vertical line and portions of the partial image along a depth; and interpolate the partial image, using the located dips within the partial image, to construct image data for the gaps of the partial image to create a full interpolated image of the formation. ### Claim 14 (depends on 13) The one or more non-transitory machine-readable media of claim 13, wherein the program code to interpolate the partial image comprises program code to cause the processor to use texture extraction techniques. ### Claim 15 (depends on 13) The one or more non-transitory machine-readable media of claim 13, wherein the location of dips in the formation within the partial image comprises of median filtering to identify the peak sections. ### Claim 16 (depends on 13) The one or more non-transitory machine-readable media of claim 13, wherein the program code to locate dips in the formation within the partial image comprises program code to cause the processor to: dip-fit peak sections across the captured images by using linear least-squares fitting; and rank potential dips based on fitting distance error, smoothness of the dips, or dip frequency deviation. ### Claim 17 (depends on 13) The one or more non-transitory machine-readable media of claim 13, wherein the program code to locate dips in the formation within the partial image comprises program code to cause the processor to incorporate a misalignment coefficient. ### Claim 18 (depends on 13) The one or more non-transitory machine-readable media of claim 13, wherein the program code to locate dips in the formation within the partial image comprises program code to cause the processor to combine peak sections that are connected to form a peak area for each portion of the partial image detected by the at least one sensor. ### Claim 19 (depends on 4) The method of claim 4, wherein dip-fitting peak sections across the captured images comprises fitting a sinusoidal curve through the peak sections across the captured images. ### Claim 20 (depends on 16) The one or more non-transitory, machine-readable media of claim 16, wherein the program code to dip-fit peak sections across the captured images comprises program code to cause the processor to fit a sinusoidal curve through the peak sections across the captured images.