An embodiment of a method of performing aspects of a downhole operation includes receiving a measurement value from a first sensor configured to measure a parameter related to the downhole operation, receiving measurement data from a different sensor, the measurement data related to the downhole operation, and performing, by a sensor evaluation module, an evaluation of the first sensor. The evaluation includes determining a condition of the first sensor based on the measurement data from the different sensor, selecting a rule that prescribes a set of one or more measurement values of the parameter that are plausible if the condition is met, and determining whether the measurement value from the first sensor is plausible based on comparing the measurement value to the prescribed set of one or more measurement values.

A method can include receiving channels of data from equipment responsive to operation of the equipment in an environment where the equipment and environment form a dynamic system; defining a particle filter that localizes a time window with respect to the channels of data; applying the particle filter at least in part by weighting particles of the particle filter using the channels of data, where each of the particles represents a corresponding time window; and selecting one of the particles according to its weight as being the time window of an operational state of the dynamic system.

A method and a system for well log data quality control is disclosed. The method includes obtaining a well log data regarding a geological region of interest, verifying an integrity and a quality of the well log data, determining the quality of the well log data based on a quality score of the well log data and making a determination regarding the access to the databases based on the quality of data. Additionally, the method includes performing the statistical analysis and the classification of well log data, a predictive and a prescriptive analysis of trends and predictions of the well log data, and generating an action plan for datasets with unsatisfactory quality scores.

One or more first sensors may be configured to sense seismic signals and one or more second sensors may be configured to sense electromagnetic crosstalk signals. The second sensors are not responsive to the seismic signals. The data from the first and second sensors may be recorded as first data and second data, respectively. The first data may be modified based on the second data to remove the electromagnetic crosstalk noise form the seismic data.

A seismic attenuation quality factor Q is determined for seismic signals at intervals of subsurface formations between a seismic source at a marine level surface and one or more receivers of a well. Hydrophone and geophone data are obtained. A reference trace is generated from the hydrophone and geophone data. Vertical seismic profile (VSP) traces are received. First break picking of the VSP traces is performed. VSP data representing particle motion measured by a receiver of the well are generated. The reference trace is injected into the VSP data. A ratio of spectral amplitudes of a direct arrival event of the VSP data and the reference trace is determined. From the ratio, a quality factor Q is generated representing a time and depth compensated attenuation value of seismic signals between the seismic source at the marine level surface and the first receiver.

Systems and methods include a computer-implemented method for characterizing low-permeability reservoirs by using numerical models. A numerical model modeling production of a well is prepared using reservoir data and well data. The numerical model is updated, including adjusting numerical model properties, until results of performing a quality assurance/quality control check indicate that the numerical model is within acceptable limits. Pressure derivatives are extracted from a transient test to create a functional numerical model. Simulations are run on the functional numerical model and reservoir features and properties are adjusted until acceptable results are achieved on: 1) a pressure match between pressures modeled in the functional numerical model and transient pressures of the well, and 2) a log-log plot derivative match between a pressure derivative of the functional numerical model and a pressure derivative of the transient pressures of the well. A simulation output that is based on the simulations is provided.

A method and system of machine learning-augmented geophysical inversion includes obtaining measured data; obtaining prior subsurface data; (a) partially training a data autoencoder with the measured data to learn a fraction of data space representations and generate a data space encoder; (b) partially training a model autoencoder with the prior subsurface data to learn a fraction of model space representations and generate a model space decoder; (c) forming an augmented forward model with the model space decoder, the data space encoder, and a physics-based forward model; (d) solving an inversion problem with the augmented forward model to generate an inversion solution; and iteratively repeating (a)-(d) until convergence of the inversion solution, wherein, for each iteration: partially training the data and model autoencoders starts with learned weights from an immediately-previous iteration; and solving the inversion problem starts with super parameters from the previous iteration.

Techniques are disclosed relating to performing marine surveys with non-uniform spacing of survey elements in a cross-line direction. This may include, for example, performing a survey pass in a multi-pass survey by towing a plurality of sources and sensors in a towing pattern with non-uniform spacing between adjacent ones of the sources. In some embodiments, the non-uniform spacing between adjacent ones of the sources is determined based on a common mid-point (CMP) spacing parameter for the survey pass in the cross-line direction. The spacing parameter may relate, for example, to difference in average CMP spacing for different parts of the survey spread, variance in CMP spacing, and/or width of the survey spread for which a threshold CMP spacing distance is satisfied. In various embodiments, the disclosed techniques may improve survey resolution and/or accuracy and may require a smaller number of survey passes and/or a reduced amount of survey equipment relative to traditional techniques.

A marine seismic streamer includes plural concentrators, plural segments interposed with the plural concentrators so that a concentrator of the plural concentrators is sandwiched between two segments of the plural segments, a first high-voltage rail HV1 that extends along the plural concentrators and the plural segments, and a second high-voltage rail HV2 that extends along the plural concentrators and the plural segments. In each given concentrator i of the plural concentrators, there is a first switch SW1 placed along one of the first high-voltage rail HV1 and the second high-voltage rail HV2, a second switch SW2 placed between the first high-voltage rail HV1 and the second high-voltage rail HV2, a first local controller implemented in hardware, and a second local controller implemented in a combination of hardware and software, and having an operating system, the first local controller being separated from the second local controller.

A method can include receiving multi-channel time series data of drilling operations; training a deep neural network (DNN) using the multi-channel time series data to generate a trained deep neural network as part of a computational simulator where the deep neural network includes at least one recurrent unit; simulating a drilling operation using the computational simulator to generate a simulation result; and rendering the simulation result to a display.