Abstract: A method for evaluating solid drilling fluid additives such as lost cuttings materials (LCM) includes acquiring a calibrated digital image of solid particles separated from drilling fluid circulating in a wellbore. The calibrated digital image is processed to identify individual ones of the solid particles depicted in the image. Color features and/or texture features are extracted from the identified solid particles depicted in the image. The extracted color and/or texture features are processed to identify LCM particles among the identified solid particles and to classify each of the identified LCM particles into one of a plurality of LCM classes and thereby obtain an LCM particle classification.

Abstract: No studies have been made regarding what kinds of refrigerants should be used in a refrigeration cycle device for a vehicle. An air conditioner (1) for a vehicle includes a refrigerant circuit (10) and a refrigerant that is sealed in the refrigerant circuit (10). The refrigerant circuit (10) includes a compressor (80), a first heat exchanger (85), which serves as a heat dissipater in a dehumidifying heating mode, an outside-air heat exchanger (82), a cooling control valve (87), and a second heat exchanger (86), which serves as an evaporator in the dehumidifying heating mode. The refrigerant is a refrigerant having a low GWP.

Abstract: Systems and methods presented herein are configured to train a neural network model using a first set of photographs, wherein each photograph of the first set of photographs depicts a first set of objects and include one or more annotations relating to each object of the first set of objects; to automatically create mask images corresponding to a second set of objects depicted by a second set of photographs; to enable manual fine tuning of the mask images corresponding to the second set of objects depicted by the second set of photographs; to re-train the neural network model using the second set of photographs, wherein the re-training is based at least in part on the manual fine tuning of the mask images corresponding to the second set of objects depicted by the second set of photographs; and to identify one or more individual objects in a third set of photographs using the re-trained neural network model.

Abstract: Systems and methods presented herein generally relate to measuring physical lithological features based on calibrated photographs of cuttings and, more specifically, to the analysis of individual cuttings that are identified in the calibrated photographs of the cuttings.

Abstract: Embodiments of the disclosure involve a method comprising a method comprising inputting borehole dip data; determining characteristics of a plurality of dips based on the borehole dip data; applying one or more geological models to the characteristics; and generating one or more geological cross-sections based on geological modeling.

Abstract: A method for determining a property of a geological formation based on an optical image of rock samples taken from the formation is presented therein. The image comprises a plurality of pixels and the method comprises defining windows in the image, each window comprising predetermined number of pixels and being of a predetermined shape. The method also includes, for each window, extracting a rockprint value representative of the window. A rockprint comprises indicators for characterizing a texture of the window. The method also includes classifying the windows into categories of a predetermined set. Each category is representative of one type of rock and the classification is based on a comparison of the rockprint value of each window with rockprint values of images of reference rock samples for each category. Based on the classification, the method then includes determining the at least one property of the geological formation, ie the quantification of each type of rock in the sample.

Abstract: The disclosure relates to methods and systems for analyzing an image of the formation intersected by a borehole. One of the methods determines a local apparent dip of the borehole at least at a measured depth i represented on the image, applies at least a window to the image, wherein each of the windows includes one of the measured depth i and is shaped as a function of the determined local dip at the corresponding measured depth i, compares a texture of at least a first zone of each window and a texture of at least a second zone of said window, wherein each of the first and second zones are adjacent and shaped as a function of the determined dip. Based on the comparison, the method determines at least a location of a texture boundary and derives a property of the formation. The other method includes determine locations of the texture boundaries, segmenting the image as a function of the texture boundaries, and perform clustering of the segments in order to determine a facies of the formation.

Abstract: Methods and systems for determining petrophysical parameters of a formation are provided. In one embodiment, a method includes acquiring formation data with a borehole imaging tool deployed in a well penetrating a formation and acquiring additional formation data with a dielectric logging tool deployed in the well. The method also includes calibrating the formation data acquired with the borehole imaging tool based on the additional formation data acquired with the dielectric logging tool. The calibrated formation data can then be used in determining a petrophysical parameter of the formation. Additional methods, systems, and devices are also disclosed.

Abstract: A method for determining a property of a geological formation based on an optical image of rock samples taken from the formation is presented therein. The image comprises a plurality of pixels and the method comprises defining windows in the image, each window comprising predetermined number of pixels and being of a predetermined shape. The method also includes, for each window, extracting a rockprint value representative of the window. A rockprint comprises indicators for characterizing a texture of the window. The method also includes classifying the windows into categories of a predetermined set. Each category is representative of one type of rock and the classification is based on a comparison of the rockprint value of each window with rockprint values of images of reference rock samples for each category. Based on the classification, the method then includes determining the at least one property of the geological formation, ie the quantification of each type of rock in the sample.

Abstract: Embodiments of the disclosure involve a method comprising a method comprising inputting borehole dip data; determining characteristics of a plurality of dips based on the borehole dip data; applying one or more geological models to the characteristics; and generating one or more geological cross-sections based on geological modeling.

Abstract: The disclosure relates to methods and systems for analyzing an image of the formation intersected by a borehole. One of the methods determines a local apparent dip of the borehole at least at a measured depth i represented on the image, applies at least a window to the image, wherein each of the windows includes one of the measured depth i and is shaped as a function of the determined local dip at the corresponding measured depth i, compares a texture of at least a first zone of each window and a texture of at least a second zone of said window, wherein each of the first and second zones are adjacent and shaped as a function of the determined dip. Based on the comparison, the method determines at least a location of a texture boundary and derives a property of the formation. The other method includes determine locations of the texture boundaries, segmenting the image as a function of the texture boundaries, and perform clustering of the segments in order to determine a facies of the formation.

Abstract: Embodiments of the disclosure involve a method comprising a method comprising inputting borehole dip data; determining characteristics of a plurality of dips based on the borehole dip data; applying one or more geological models to the characteristics; and generating one or more geological cross-sections based on geological modeling.

Abstract: Apparatus and methods for use with borehole image data to: delineate a dip and/or a fracture from the borehole image data; create a gap-filled image from the borehole image data; extract a fracture segment from the borehole image data; determine matrix information from the borehole image data; delineate a heterogeneity from the borehole image data; and analyze image porosity. The image porosity analysis is based on: the dip and/or fracture delineated from the borehole image data; the gap-filled image created from the borehole image data; the fracture segment extracted from the borehole image data; the matrix information determined from the borehole image data; and the heterogeneity delineated from the borehole image data.

Abstract: Methods and systems for determining petrophysical parameters of a formation are provided. In one embodiment, a method includes acquiring formation data with a borehole imaging tool deployed in a well penetrating a formation and acquiring additional formation data with a dielectric logging tool deployed in the well. The method also includes calibrating the formation data acquired with the borehole imaging tool based on the additional formation data acquired with the dielectric logging tool. The calibrated formation data can then be used in determining a petrophysical parameter of the formation. Additional methods, systems, and devices are also disclosed.

Abstract: Embodiments of the disclosure involve a method comprising a method comprising inputting borehole dip data; determining characteristics of a plurality of dips based on the borehole dip data; applying one or more geological models to the characteristics; and generating one or more geological cross-sections based on geological modeling.

Abstract: Apparatus and methods for use with borehole image data to: delineate a dip and/or a fracture from the borehole image data; create a gap-filled image from the borehole image data; extract a fracture segment from the borehole image data; determine matrix information from the borehole image data; delineate a heterogeneity from the borehole image data; and analyze image porosity. The image porosity analysis is based on: the dip and/or fracture delineated from the borehole image data; the gap-filled image created from the borehole image data; the fracture segment extracted from the borehole image data; the matrix information determined from the borehole image data; and the heterogeneity delineated from the borehole image data.

Abstract: A vehicle seat with a function of absorbing volatile substances in an interior of a vehicle with the seat is disclosed. The vehicle seat comprises a seat frame structure, a cushioned padding member supported on the seat frame structure, and a volatile substances-absorbing member provided on a surface of the cushioned padding member which faces the seat frame structure.

Abstract: A vehicle seat with a function of absorbing volatile substances in an interior of a vehicle with the seat is disclosed. The vehicle seat comprises a seat frame structure, a cushioned padding member supported on the seat frame structure, and a volatile substances-absorbing member provided on a surface of the cushioned padding member which faces the seat frame structure.

Abstract: A power reception apparatus receives feed information from a predetermined line of a communication cable and judges a state of the power reception apparatus. If the state is normal, it transmits the feed information by returning it to a line which is a pair with the predetermined line.

Abstract: A vehicle seat with a function of absorbing volatile substances in an interior of a vehicle with the seat is disclosed. The vehicle seat comprises a seat frame structure, a cushioned padding member supported on the seat frame structure, and a volatile substances-absorbing member provided on a surface of the cushioned padding member which faces the seat frame structure.