A method may comprise forming a data matrix, extracting chromatographs of a mud filtrate and a formation fluid, extracting concentration profiles of the mud filtrate and the formation fluid, and decomposing a data set on an information handling machine using a bilinear model. A system may comprise a downhole fluid sampling tool and an information handling tool. The downhole fluid sampling tool may comprise one or more multi-chamber sections, one or more fluid module sections, one or more gas chromatographers, wherein the one or more gas chromatographers are disposed in the one or more fluid module sections, and an information handling system.

A method is provided for determining a lithology of a subterranean formation into which a wellbore has been drilled. The method includes receiving a set of measurement logs including one or more measurement logs, each representing a measured characteristic of the wellbore plotted according to depth. The method also includes segmenting the wellbore into regions based on identified change of trend in one or more of the measurement logs of the set, and sub-segmenting at least one region into zones based on detection of appearance or disappearance of a rock type in the cuttings percentage log, The method also includes determining, in each zone, a location, length and rock type of one or more layers based on a total percentage of each rock type in the zone in the cuttings percentage log and at least one of the additional measurement logs.

A modular system for analyzing drilled cuttings includes a sampler unit, a washer unit, an analysis unit, and a central processing unit. The sampler unit receives the drilled cuttings from a shale shaker disposed on a rig site that obtains the drilled cuttings. The washer unit removes debris from the drilled cuttings. The analysis unit determines lithological properties of the drilled cuttings. The packager unit packages the drilled cuttings. The central processing unit coordinates operations to process the drilled cuttings through each of the sampler unit, washer unit, analysis unit and packager unit. The central processing unit facilitates a processing link among the sampler unit, washer unit, analysis unit and packager unit so that the sampler unit, washer unit, analysis unit and packager unit are integrated to form the modular system.

A method of designing a cement blend for a wellbore isolation barrier based on the analysis of a stress state of the wellbore isolation barrier from the injection of CO.sub.2 into a porous formation. The analysis software may determine an optimized cement blend for a future CO.sub.2 injection schedule. The analysis software may determine a current near wellbore stress state for a current CO.sub.2 injection schedule. The analysis software may optimize a CO.sub.2 injection schedule based on the analysis of a future near wellbore stress state of the wellbore isolation barrier. The near wellbore stress state of the isolation barrier may be determined by at least one model accessed by the analysis software. The inputs into the model comprise periodic CO.sub.2 injection pressure and flowrate datasets, cement properties, and formation properties.

Systems and methods for this disclosure describe systems and methods that are directed to monitoring active clay in water-based drilling fluid may be provided. A method for monitoring active clay concentration while drilling may be provided. The method may include providing a sample of water-based drilling fluid. The method may further include adding methylene blue to the sample in a methylene blue titration. The method may further include performing an impedance measurement on the sample during the methylene blue titration. The method may further include determining an endpoint of the methylene blue titration using a phase angle measurement from the impedance measurement. The method may further include correlating the endpoint to the active clay concentration of the sample. The method may further include determining a treatment for the water-based drilling fluid based on the active clay concentration.

Drilling process methods and systems for drilling are described. The methods include performing a drilling operation through a downhole formation, the drilling operation generating drilling cuttings. A single drilling cuttings sample is obtained at a surface-based location. X-ray diffraction (XRD) and/or x-ray fluorescence (XRF) analysis are performed on the single drilling cuttings sample. Element information and mineral information of the single drilling cuttings sample is obtained from the XRF analysis regarding the downhole formation. From the obtained information, a determination of at least one rock petrophysics property of the downhole formation is made.

A method for estimating in-situ porosity based on cutting images employs a neural network trained with labeled images, the labels indicating wireline porosity values. The method may be used to obtain porosity values along a vertical, deviated or horizontal well, where wireline logging data is not available or unreliable. The method uses machine learning. Training and validating the neural network may be ongoing processes in the sense that any new labeled image that becomes available can be added to the training set and the neural network being retrained to enhance its predictive performance.

An advanced geological prediction method and system based on perception while drilling, and relates to advanced geological prediction. The solution includes: acquiring drilling parameters during drilling; obtaining physical and mechanical parameters of tunnel surrounding rocks by inversion based on drilling parameters; acquiring rock slag or powder based on flushing fluid collected during drilling; acquiring geochemical characteristic parameters of rock slag or powder; and obtaining at least one adverse geology recognition result and surrounding rock classification result using a pre-trained deep learning model, and realizing advanced geological prediction. Combined with advanced geological drilling, the solution reflects geological characteristics from changes of physical and mechanical properties of tunnel surrounding rocks and changes of geochemical characteristic parameters. Advanced prediction of geology ahead of a tunnel face is realized by collection and analysis of drilling parameters and flushing fluid during advanced drilling and the fusion of big data and a deep learning algorithm.

Compositions and methods for determining the origin location of a subterranean sample are provided. Compositions include a polymer-clay composite tag. The tag includes a nanoclay including a plurality of layers, and a polymer intercalated between the layers of the nanoclay. The polymer is functionalized with a fluorescent dye. A method to determine the origin location of a subterranean sample includes mixing a barcoded polymer-clay composite tag into a fluid, flowing the fluid through a work string into a subterranean formation, recovering subterranean samples from the subterranean formation, and determining the origin location of the subterranean sample by detecting the presence of the barcoded polymer-clay composite tag.

A system, method, and apparatus for real-time characterization of drilled particles during a drilling operation can be comprised of a light illumination source to output short-wave-infrared (SWIR) light toward the drilled particles as the drilled particles exit a drill hole being drilled by a drilling machine; a sensor to sense reflected short-wave-infrared (SWIR) light reflected from the drilled particles exiting the drill hole; and processing circuitry operatively coupled to at least the sensor. The processing circuitry can be configured to determine a spectrum of the reflected short-wave-infrared light sensed by the sensor, and determine particle characterization for a portion of the drilled particles by performing hyperspectral analysis on the determined spectrum and based on predetermined candidate particle characterizations.