Abstract: Lines of existing data are extrapolated to provide additional lines of seismic data by using small inline gates of existing cables. At each frequency slice of a space gate on the existing cables, a 2-D prediction error filter that can predict the data in forward and backward directions is designed. A prediction filter is obtained from the prediction error filter and applied to a cable at an edge of the space gate to predict a first missing cable. By repeating this process using overlapping inline gates, overlapping inline gates of the extrapolated cables may be obtained. By suitable weighting of the inline gates of the extrapolated cables, a complete cable length is extrapolated. The process may be repeated using the first extrapolated cable in the derivation to give additional extrapolated cables. The invention may be used for interpolating cables of dealiased cables between existing cables using a masking and filtering operation in the frequency-wave number domain.

Abstract: Lines of existing data are extrapolated to provide additional lines of seismic data by using small inline gates of existing cables. At each frequency slice of a space gate on the existing cables, a 2-D prediction error filter that can predict the data in forward and backward directions is designed. A prediction filter is obtained from the prediction error filter and applied to a cable at an edge of the space gate to predict a first missing cable. By repeating this process using overlapping inline gates, overlapping inline gates of the extrapolated cables may be obtained. By suitable weighting of the inline gates of the extrapolated cables, a complete cable length is extrapolated. The process may be repeated using the first extrapolated cable in the derivation to give additional extrapolated cables. The invention may be used for interpolating cables of dealiased cables between existing cables using a masking and filtering operation in the frequency-wavenumber domain.

Abstract: A method for controlling the position and shape of marine seismic streamer cables, whereby a plurality of real time signals from a marine seismic data acquisition system and a plurality of threshold parameters from an input device are received. The real time signals are compared to the threshold parameters to determine if the streamer cables should be repositioned. The streamer cables are repositioned when the real time signals exceed the threshold parameters.

Abstract: Wide-angle reflections that have been overcorrected using a simple two-term hyperbolic moveout correction are adjusted by application of a bi-quadratic term. The biquadratic term is derived by scanning the overcorrected reflections for residual velocity. The residual velocity is used to calculate an adjustment as a linear function of the first power of the travel time to each receiver versus the fourth power of the corresponding receiver offset.

Abstract: A high-order polynomial regression curve is fitted to a global set of first arrival times as a function of the nominal ranges between a plurality of acoustic sources having known geodetic coordinates and a plurality of acoustic detectors whose coordinates are imperfectly known. The order of the polynomial is chosen to be that order that minimizes the variance of the parameters about the regression curve. The polynomial is used as a quasi-velocity function for iteratively optimizing the best estimate of the ranges between each detector and every source station. The best estimate of the detector position is derived by multi-lateration using the computed ranges.

Abstract: A computer-aided method for providing a de-aliased output data set d.sub.L (t,x.sub.L,y.sub.L) from a spatially aliased, three-dimensional, input data set of known seismic signals, a(t,x,y), where L is an interpolator. The known data set is zero-padded by L. The zero-padded data set is zero-masked. The zero-padded data set is divided by a zero-padded, zero-masked data set to provide an interpolation operator H.sub.L. L-1 zero traces are interleaved between the known traces of data set a(t,x,y) to provide a zero-inserted data set c.sub.L ((t,x.sub.L,y.sub.L) whose transform is C.sub.L (m,k.sub.xL,k.sub.yL). The product of (H.sub.L) with (C.sub.L) is (D.sub.L) which is inverse-transformed to provide the desired de-aliased data set d.sub.L (t,x.sub.L,y.sub.L).