Abstract:
Systems and methods of engineering the optical properties of an optical Integrated Computational Element device using ion implantation during fabrication are provided. A system as disclosed herein includes a chamber, a material source contained within the chamber, an ion source configured to provide a high-energy ion beam, a substrate holder to support a multilayer stack of materials that form the Integrated Computational Element device, a measurement system, and a computational unit. The material source provides a material layer to the multilayer stack, and at least a portion of the ion beam is deposited in the material layer according to an optical value provided by the measurement system.
Abstract:
An optical computing device comprising a plurality of electromagnetic radiation sources, each at a unique angular displacement about an optical train and each at at least one unique electromagnetic radiation wavelength; an integrated computational element (ICE) located in the optical train before or after a sample located in the optical train to generate modified electromagnetic radiation in the optical train; a broadband angle-selective filter (BASF) located in the optical train that is rotatable about an axis to a plurality of unique orientations to transmit the electromagnetic radiation and/or the modified electromagnetic radiation in the optical train at a target incident angle corresponding to one of the plurality of electromagnetic radiation sources to generate angle selected-modified electromagnetic radiation (ASMR); and a detector to receive the ASMR and to generate an output signal corresponding to a characteristic of the sample.
Abstract:
Methods and systems for manufacturing optical computing elements, including a method for correcting element layer thickness measurements during manufacturing that includes depositing an element layer on a glass substrate or a previously deposited layer, illuminating the deposited layer and sampling reflected or transmitted light produced by said illuminating, detecting and measuring an actual magnitude of the sampled light as a function of wavelength, and modeling the sampled light to produce a predicted magnitude of the sampled light. The method further includes determining a discrepancy between the actual and predicted magnitudes, adjusting the actual magnitude based on said discrepancy, calculating the thickness of the deposited layer based upon the adjusted actual magnitude of the sampled light, and adjusting the deposited layer's thickness if the calculated thickness is not within a tolerance range of a target thickness.
Abstract:
Systems and methods of controlling a deposition rate during thin-film fabrication are provided. A system as provided may include a chamber, a material source contained within the chamber, an electrical component to activate the material source, a substrate holder to support the multilayer stack and at least one witness sample. The system may further include a measurement device and a computational unit. The material source provides a layer of material to the multilayer stack and to the witness sample at a deposition rate controlled at least partially by the electrical component and based on a correction value obtained in real-time by the computational unit. In some embodiments, the correction value is based on a measured value provided by the measurement device and a computed value provided by the computational unit according to a model.
Abstract:
A method and system for performing a pressure test. The method may comprise inserting a formation testing tool into a wellbore to a first location within the wellbore, identifying one or more tool parameters of the formation testing tool, performing a first pre-test with the pressure transducer when the pressure has stabilized to identify formation parameters, inputting the formation parameters and the one or more tool parameters into a forward model, changing the one or more tool parameters to a second set of tool parameters; performing a second pre-test with the second set of tool parameters; and comparing the first pre-test to the second pre-test. A system may comprise at least one probe, a pump disposed within the formation testing tool, at least one stabilizer, a pressure transducer disposed at least partially in the at least one fluid passageway, and an information handling system.
Abstract:
A method for designing a tool string for use in a wellbore includes receiving a merit function, and determining, with a computing system and based on the merit function, a tool string design for a tool string. The merit function comprises one or more defined objectives for performing a process in a wellbore. The tool string design comprises an indication of one or more tools used to form a tool string for performing the process in the wellbore, and the tool string design satisfies the merit function.
Abstract:
Embodiments of a device, system and method are disclosed herein. In one embodiment, a device comprises a sample cell configured to interact a fluid sample with an ion selective substrate to modify an optical characteristic of the ion selective substrate according to an ion concentration of the fluid sample, wherein the sample cell is also configured to optically interact an illumination light with the ion selective substrate to generate a sample light; an optical element configured to interact with the sample light to provide a modified light that has a property of the fluid sample; and a detector that receives the modified light and provides an electrical signal proportional to the property of the fluid sample indicated by the modified light; and wherein the ion selective substrate comprises a membrane, the membrane configured to change an optical property in a selected wavelength range, according to the property of the fluid sample.
Abstract:
The subject disclosure provides for a method of optical sensor calibration implemented with neural networks through machine learning to make real-time optical fluid answer product prediction adapt to optical signal variation of synthetic and actual sensor inputs integrated from multiple sources. Downhole real-time fluid analysis can be performed by monitoring the quality of the prediction with each type of input and determining which type of input generalizes better. The processor can bypass the less robust routine and deploy the more robust routine for remainder of the data prediction. Operational sensor data can be incorporated from a particular optical tool over multiple field jobs into an updated calibration when target fluid sample compositions and properties become available. Reconstructed fluid models adapted to prior field job data, in the same geological or geographical area, can maximize the likelihood of quality prediction on future jobs and optimize regional formation sampling and testing applications.
Abstract:
Systems, methods, and computer-readable media for detecting downhole environment characteristics. An optical sensor is deployed to a downhole environment. Optical signal data received from the deployed optical sensor is received by a model configured to determine downhole environment characteristics directly from optical signal data. The model determines a downhole environment characteristic from the optical signal data and provides the determined characteristic to a user.
Abstract:
A method may comprise sampling a wellbore fluid; analyzing the wellbore fluid and determining a presence of a graphene-like substrate, a concentration of the graphene-like substrate, or both, in the wellbore fluid; and correlating the presence and the concentration of the graphene-like substrate to at least one subterranean formation characteristic.