Jan Brouwer

Shallow to very shallow, high‐resolution reflection seismic using a portable vibrator system

In shallow engineering‐geophysical applications, there is a lack of controlled, nondestructive, high‐resolution mapping tools, particularly for the target depth that ground‐penetrating radar cannot reach but which is too shallow for other conventional geophysical methods. For soft soil, this corresponds to a depth of 2 to 30 m. We have developed a portable, high‐frequency P-wave vibrator system that is capable of bridging this gap. As far as the important contribution of the seismic source is concerned, penetration and resolution can be individually controlled through easy modulation of the sweep signal generated by this electromagnetic vibrator. The feasibility of this system has been tested in shallow (10–50 m) to very shallow (0–10 m) applications. Seven field data sets representing varying geology, site conditions, and exploration targets are presented to illustrate the applicability. The first three examples show the potential of this portable vibrator source in shallow applications. Under favorable ...

Estimation of changes in saturation and pressure from 4D seismic AVO and time-shift analysis

A reliable estimate of reservoir pressure and fluid saturation changes from time-lapse seismic data is difficult to obtain. Existing methods generally suffer from leakage between the estimated parameters. We propose a new method using different combinations of time-lapse seismic attributes based on four equations: two expressing changes in prestack AVO attributes (zero-offset and gradient reflectivities), and two expressing poststack time-shifts of compressional and shear waves as functions of production-induced changes in fluid properties. The effect of using different approximations of these equations was tested on a realistic, synthetic reservoir, where seismic data have been simulated during the 30-year lifetime of a water-flooded oil reservoir. Results found the importance of the porosity in the inversion with a clear attenuation of the porosity imprint on the final estimates in case the porosity field or the vertically averaged porosity field is known a priori. The use of a first-order approximation of the gradient reflectivity equation leads to severely biased estimates of changes in saturation and leakage between the two different parameters. Both the bias and the leakage can be reduced, if not eliminated, by including higher-order terms in the description of the gradient, or by replacing the gradient equation with P- and/or S-wave time-shift data. The final estimates are relatively robust to random noise, as they present fairly high accuracy in the presence of white noise with a standard deviation of 15%. The introduction of systematic noise decreases the inversion accuracy more severely.

The improvement of geotechnical subsurface models through the application of S-wave reflection seismic exploration

Due to its relatively high sensitivity to the distribution of elastic parameters, the seismic technique is quite suitable for geotechnical subsurface investigations. However, practical implementation of the P-wave exploration technique for soft-soil and shallow-groundwater conditions, as often encountered in the Netherlands, may often prove problematic; the highimpedance contrast at the groundwater table may induce strong reverberations and guided waves, resulting in a distortion of the seismic record at shallow depth. The use of buried sources may be of some advantage, but at the cost of a considerable decrease in the speed of operation.

The Importance of Localization In the Assimilation of 4D Seismic Data In the Data Assimilation Process Using the EnKF

The Ensemble Kaiman Filter (EnKF) is considered a fast and efficient algorithm in the data assimilation process to estimate reservoir properties from measured data. 4D seismics is an important source of information for the reservoir monitoring and the improvement of the geological model. The use of low frequencies for deep surface seismic makes it very complicated to discriminate and estimate properties for fine-grid reservoir models. In this paper it is demonstrated that using vertically averaged seismic data, inverted as time-lapse differences in pore pressure and saturation, greatly improves the quality of the history match and the estimation of the reservoir state. The EnKF may present some problems when assimilating large amounts of data (frequent 4D seismic), as the flexibility of the model solution is strongly reduced. The conditioning of the covariance matrix in the Kaiman gain is a key to avoid the filter divergence. In this study the localization criterion is based on the mere distance or on the streamlines trajectories. Results from 2D and 3D synthetic examples show the importance of localization to ensure the correct functioning of the filter.