Westerngeco L.l.p.

Schlumberger Technology Corporation

Westerngeco Seismic Holdings Limited

Geco Technology B.v.

Ali Ozbek

Ahmet Kemal Ozdemir

Massimiliano Vassallo

Dirk-Jan Van Manen

James Edward Martin

Riadh Boualleg

Bent Andreas Kjellesvig

Philippe Caprioli

Ling Li

Reza Taherian

Robert Montgomery Laws

Ralf Ferber

Julian Edward Kragh

Johan Olof Anders Robertsson

David Fraser Halliday

Johan O A Robertsson

Jon-Fredrik Hopperstad

Simon Hastings Bittleston

Jaideva C Goswami

Valerian Guillot

Bassem Khadhraoui

Ying Ji

James Martin

Yousif Izzeldin Kamil Amin

Susanne Rentsch-Smith

Nils Lunde

Florian Karpfinger

Julian Drew

Nihed El Allouche

Jason Gardner

Wouter Gerrit Brouwer

Daniel Gordon Raymer

Amit Mukherjee

Ahmet Kemal Özdemir

Anthony Probert

Peter Forman

A method to design well trajectories includes determining dogleg severity as a function of inclination, and a corresponding rate of penetration performance of the tool by a hybrid model including physical modelling and machine learning correction. The method includes solving for optimal steering parameters to predict a dogleg severity as close as possible to a desired dogleg severity at a given inclination of the trajectory, which is repeated for dogleg severity and inclination combinations of interest. The rate of penetration for feasible points is also determined and a rate of penetration (or time-to-target) map can be produced. Potential trajectories are then evaluated relative to the map to estimate drilling time-to-target, and an optimal trajectory can be selected that has a lowest time-to-target while also being feasible for the tool and optionally avoiding risks or downhole obstacles.

Optimization based on predicted tool performance

Well planning based on hazard predictive models

A method can include receiving data acquired via survey equipment disposed in an environment; analyzing at least a portion of the data via an iterative adaptive approach that implements matching pursuit to generate analysis results; and identifying at least one feature in the environment based at least in part on a portion of the analysis results.

Compressive sensing imaging

A system and method for multicomponent noise attenuation of a seismic wavefield is provided. Embodiments may include receiving, at one or more computing devices, seismic data associated with a seismic wavefield over at least one channel of a plurality of channels from one or more seismic sensor stations. Embodiments may further include identifying a noise component on the at least one channel of the plurality of channels and attenuating the noise component on the at least one channel of the plurality of channels based upon, at least in part, the seismic data received from the one or more seismic sensor stations.

Land seismic sensor spread with adjacent multicomponent seismic sensor pairs on average at least twenty meters apart

Seismic data processing using one or more non-linear stacking enabling detection of weak signals relative to noise levels. The non-linear stacking includes a double phase, a double phase-weighted, a real phasor, a squared real phasor, a phase and an N-th root stack. Microseismic signals as recorded by one or more seismic detectors and transformed by transforming the signal to enhance detection of arrivals. The transforms enable the generation of an image, or map, representative of the likelihood that there was a source of seismic energy occurring at a given point in time at a particular point in space, which may be used, for example, in monitoring operations such as hydraulic fracturing, fluid production, water flooding, steam flooding, gas flooding, and formation compaction.

Processing seismic data by nonlinear stacking

A method for processing microseismic data, comprises: receiving the microseismic data acquired by one or more multicomponent sensors; convolving the microseismic data with an operator that is applied to all of the components of the microseismic data; and applying a multicomponent filter operator to the convolved microseismic data. The microseismic data may result from human activity or be entirely natural. The filtering preserves the polarity of the received data while improving the signal-to-noise ratio of the filtered data.

Noise attenuation of multicomponent microseismic data

A technique includes receiving seismic data indicative of measurements acquired by seismic sensors. The measurements are associated with a measurement noise. The technique includes estimating at least one characteristic of the measurement noise and deghosting the seismic data based at least in part on the estimated characteristic(s) of the measurement noise.

Deghosting and interpolating seismic data

A technique for reconstructing a seismic wavefield includes receiving data over one or more channels of a plurality of channels from a plurality of stations. The data is recorded by a plurality of seismic receivers and represent measurements of properties of the seismic wavefield. Each station includes a region in space including one or more seismic receivers. Each channel either measures a property of the seismic wavefield or a property of the seismic wavefield after the seismic wavefield has undergone a known transformation. At least one channel is derived as a function of one or more other channels. The technique includes using a processor based machine to process the data to model the seismic wavefield as a sum of basis functions; apply to the basis functions at least one forward transformation that describes the measurements received over the channel(s); and determine optimum basis functions based at least in part on the measurements.

Wavefield reconstruction

A technique includes spatially filtering a signal that is derived from a seismic acquisition. The filtering is associated with a filter length, and the filtering includes varying the filter length with frequency. The filtering may be used in connection with adaptive noise attenuation, which is applied to decomposed subbands. Furthermore, the filtering may be applied during the reconstruction of the signal from the subbands.

Removing noise from a seismic measurement

A technique includes receiving sensor data; sorting the data into a gather representation that corresponds to a plurality of shots of an energy source; and determining a signal cone based at least in part on at least one characteristic of the gather representation. The technique includes processing the sensor data in a processor-based machine to attenuate noise to generate data representing a signal based at least in part on the determined signal cone and the gather representation.

Attenuating noise acquired in an energy measurement

There is provided a method of interpolating wave signals, particularly seismic signals acquired through a seismic survey, using the steps of obtaining time series of measured wave signals; and selecting iteratively basis functions to represent said measured signals with a basis function being fully defined by n parameters, wherein in each iteration one or more basis functions are combined with the selected basis functions such that the residual between the measured signals and a representation of the measured signal by the combined basis functions is minimized at the locations of the measurement at each iteration.

Method of representing seismic signals

A technique includes estimating propagation parameters that are associated with a towed seismic survey based at least in part on seismic signal measurements and noise measurements.

System and technique to estimate physical propagation parameters associated with a seismic survey

A technique includes representing actual measurements of a seismic wavefield as combinations of an upgoing component of the seismic wavefield and ghost operators. Interpolated and deghosted components of the seismic wavefield are jointly determined based at least in part on the actual measurements and the representation.

Jointly interpolating and deghosting seismic data

There is provided a method of spatially shifting seismic signals acquired through a seismic survey using the steps of identifying within the signals a set of N actual locations of seismic receivers and corresponding N seismic signals received by the set of seismic receivers; identifying a set of N' desired locations of seismic receivers; and determining a set of N&#x2032; signal values at said N&#x2032; desired locations by evaluating for each of said N&#x2032; signal values a weighted sum of the N seismic signals, wherein the weights are at least partly determined by the relative distance between pairs of locations selected from said set of N actual locations of seismic receivers.

Regularisation of irregularly sampled seismic data

A technique includes modeling interpolated seismic measurements as a random process characterized by seismic measurements acquired at a set of sensor locations and an interpolation error. The technique includes determining the interpolated seismic measurements based at least in part on a minimization of the interpolation error.

Growing community of inventors

Milton, United Kingdom

Ali Ozbek