Abstract: Methods and systems are provided for downhole analysis of formation fluids by deriving fluid properties and associated uncertainty in the predicted fluid properties based on downhole data, and generating answer products of interest based on differences in the fluid properties. Measured data are used to compute levels of contamination in downhole fluids using an oil-base mud contamination monitoring (OCM) algorithm. Fluid properties are predicted for the fluids and uncertainties in predicted fluid properties are derived. A statistical framework is provided for comparing the fluids to generate, in real-time, robust answer products relating to the formation fluids and reservoirs thereof. Systematic errors in measured data are reduced or eliminated by preferred sampling procedures.

Abstract: The present invention is directed to methods and systems for taking measurements relating to subterranean formations. The methods and systems effectively compress data and thus facilitate more efficient data transmission. The methods and systems are capable of automatically varying data compression rates during a measurement operation. The variable data compression capability facilitates reliable collection of measurement data at faster and/or constant logging speeds. The data compression methods and systems may be applied to any measurement operation relating to subterranean formations, including, but not limited to: acoustic wireline logging measurements, acoustic logging-while-drilling measurements, electromagnetic measurements, nuclear magnetic resonance measurements, and resistivity measurements.

Abstract: A method of determining the sonic slowness of a formation traversed by a borehole comprising generating tracks from sonic waveform peaks received at a plurality of depths wherein the peaks that are not classified prior to tracking is set forth. A method for generating a slowness versus depth log is generated for waveform arrivals by classifying long tracks, classifying small tracks; classifying tracks that overlap; filling in gaps; and creating a final log is disclosed. In further improvements, non-classified tracks and interpolation are used to fill in gaps.

Abstract: Methods and systems for taking measurements related to subterranean formations. The methods and systems provide robust, reliable first arrival data for component signals of interest, which may be used to estimate formation slowness, characterize formation slowness zones, or act as an input to other processes. The methods and systems are capable of automatically providing good first arrival data based on signals received without any human interaction, and without setting or changing any parameters.

Abstract: A method and apparatus for determining isolating and/or removing a signal of interest from acoustic data. The method and apparatus may be used to measure formation slowness in a cased borehole, in which case the signal of interest may be a casing arrival signal. The casing arrival signal may be detected, rebuilt and removed from a set of acoustic data. Semblance processing is applied to the acoustic data with the casing signal removed, yielding a coherent formation slowness log. A filter band may be defined and automatically administered to detect and remove the signal of interest such as the casing signal.

Abstract: A method of determining the sonic slowness of a formation traversed by a borehole comprising generating tracks from sonic waveform peaks received at a plurality of depths wherein the peaks that are not classified prior to tracking is set forth. A method for generating a slowness versus depth log is generated for waveform arrivals by classifying long tracks, classifying small tracks; classifying tracks that overlap; filling in gaps; and creating a final log is disclosed. In further improvements, non-classified tracks and interpolation are used to fill in gaps.

Abstract: A method and apparatus for determining isolating and/or removing a signal of interest from acoustic data. The method and apparatus may be used to measure formation slowness in a cased borehole, in which case the signal of interest may be a casing arrival signal. The casing arrival signal may be detected, rebuilt and removed from a set of acoustic data. Semblance processing is applied to the acoustic data with the casing signal removed, yielding a coherent formation slowness log. A filter band may be defined and automatically administered to detect and remove the signal of interest such as the casing signal.

Abstract: Methods for determining the best value for at least one slowness-related parameter that has been determined in a number of ways is disclosed. Sonic logging data input in the methods are processed to determine multiple values of at least one slowness-related parameter using slowness/time coherence (STC) processing methods. The error of each determined parameter is determined and the determined errors used in selecting a representative parameter value from the multiple determined slowness-related parameter values.

Abstract: A method of determining the sonic slowness of a formation traversed by a borehole comprising generating tracks from sonic waveform peaks received at a plurality of depths wherein the peaks that are not classified prior to tracking is set forth. A method for generating a slowness versus depth log is generated for waveform arrivals by classifying long tracks, classifying small tracks; classifying tracks that overlap; filling in gaps; and creating a final log is disclosed.

Abstract: Methods for downhole waveform tracking and sonic labeling employ “tracking algorithms” and Bayesian analysis to classify STC waveforms. More particularly, according to the tracking part of the invention, a probability model is built to distinguish true “arrivals” (e.g. compressional, shear, etc.) from “false alarms” (e.g. noise) before the arrivals are classified. The probability model maps the “continuity” of tracks (slowness/time over depth) and is used to determine whether sequences of measurements are sufficiently “continuous” to be classified as tracks. The probability model is used to evaluate the likelihood of the data in various possible classifications (hypotheses). Prior and posterior probabilities are constructed for each track using the tracking algorithm. The posterior probabilities are computed sequentially and recursively, updating the probabilities after each measurement frame at depth k is acquired.

Abstract: Methods for processing sonic logging data obtained from a logging tool having an array of R receivers, includes selecting a sub-array size of Rsb receivers where Rsb<R; calculating the number of sub-arrays Nsb possible from the array of R receivers; identifying one receiver Rref in the array to serve as a reference receiver for each sub-array; processing data in the slowness-time plane for each sub-array with respect to the reference receiver Rref; and stacking the processed data in the slowness-time plane for all sub-arrays.