Ben Witten

Signal-to-noise estimates of time-reverse images

Locating subsurface sources from passive seismic recordings is difficult when attempted with data that have no observable arrivals and/or a low signal-to-noise ratio (S/N). Energy can be focused at its source using time-reversal techniques. However, when a focus cannot be matched to a particular event, it can be difficult to distinguish true focusing from artifacts. Artificial focusing can arise from numerous causes, including noise contamination, acquisition geometry, and velocity model effects. We present a method that reduces the ambiguity of the results by creating an estimate of the (S/N) in the image domain and defining a statistical confidence threshold for features in the images. To do so, time-reverse imaging techniques are implemented on both recorded data and a noise model. In the data domain, the noise model approximates the energy of local noise sources. After imaging, the result also captures the effects of acquisition geometry and the velocity model. The signal image is then divided by the noise image to produce an estimate of the (S/N). The distribution of image (S/N) values due to purely stochastic noise provides a means by which to calculate a confidence threshold. This threshold is used to set the minimum displayed value of images to a statistically significant limit. Two-dimensional synthetic examples show the effectiveness of this technique under varying amounts of noise and despite challenging velocity models. Using this method, we collocate anomalous low-frequency energy content, measured over oil reservoirs in Africa and Europe, with the subsurface location of the productive intervals through 2D and 3D implementations.

Quaternion-based Signal Processing

Hypercomlex numbers, which have primarily been used for pattern recognition, offer many useful applications to geophysics. Image disparity estimation is a hypercomplex, phase-based technique, using quaternions, that can nd differences between subtlety varying images. This technique relies on applying a quaternionic Fourier transform, a quaternionic Gabor lter and exploits the symmetries inherent in the quaternion. Two applications of hypercomplex image disparity estimation are time lapse analysis and boundary detection.

Extended imaging conditions for passive seismic data

Seismic monitoring at injection sites (e.g., CO2 sequestration, hydraulic fracturing) has become an increasingly common tool amongst oil and gas producers. The information obtained from these data is often limited to seismic event properties (e.g., location, initiation time, moment tensor), the accuracy of which greatly depends on the assumed or estimated elastic velocity models. However, estimating accurate 3D velocity models from passive array data remains a challenging problem. Extended imaging conditions (eICs) for passive wave-equation imaging algorithms represent a key step towards generating - and verifying - elastic velocity models. By extending imaging conditions away from zero-lag in time and space we can better evaluate the focusing of a given event based on the principle that waves focus at zero lag only when the velocity models are “correct”. We demonstrate that given an elastic medium and multi-component recordings, we can propagate and correlate microseismic P- and S-wavefield modes to compute eICs for P- and S- velocity perturbations. We observe that the maximum correlation deviates from the zero-lag in time and space for a P/S cross-correlation imaging condition when using an incorrect P- and/or S-wave velocity, and thus there is sensitivity to velocity error not observable when using individual wavefield components.

Geophysical remote sensing of a historical aboriginal gravesite in Quairading, Western Australia

Burial sites have extreme cultural significance to societies around the world. Until recently, insufficient recognition of Aboriginal heritage in Australia has led to a very poor understanding and documentation of many culturally significant locations, including burial sites. In some cases, sites have been preserved through the efforts of local people; however, others were subsequently redeveloped or even completely destroyed. Local Aboriginal people are usually the best source of information regarding these locations and can identify broad regions with historical significance, but seldom do they provide precise details about individual grave locations. There are still many Aboriginal gravesites throughout Australia where the exact burial locations are unknown. Locating gravesites - and doing so in a way that minimises site disturbance - is paramount to any investigation and preservation program. For efficient investigation of large areas, geophysical remote sensing provides practical and non-invasive tools for investigation of large poorly documented burial areas. The UWA Society of Exploration Geophysicists Student Chapter, in conjunction with the South West Aboriginal Land and Sea Council, acquired several near-surface geophysical surveys over a known aboriginal burial site near Quairading, Western Australia. Multiple techniques were used to delineate possible grave locations, including ground penetrating radar (GPR), magnetics and conductivity. While work is ongoing with the data processing and integration, and future surveys are planned, early indications show anomalies that may be related to burial locations.

Imaging Using the Ambient Wave Field; Low-frequency Seismic Imaging of an Unproduced Oil Reservoir In Egypt

A low frequency (LF) passive seismic survey was acquired in Egypt over a discovered but unproduced oil reservoir. Sixty hours of synchronous data were recorded on an array of stations in several lines over the oil discovery and adjacent prospects. The survey design allowed for the implementation of 3D Time-Reverse Imaging (TRI). Quiet portions of the recorded wave field refocused in the subsurface at the discovery well and at least one of the prospective surrounding fault blocks. The TRI data volume was loaded and interpreted on a G&G workstation using a work flow developed to rigorously analyze this new data type. A series of experiments were conducted to test the sensitivity of the results to changes in the input data and velocity model.