An Application Of Optical Flow To Time-Lapse Analysis In 2-D Seismic Images

Abstract

Time-lapse (4-D) seismic reservoir monitoring is a relative new technology that is gaining recognition in oil and gas producing areas around the world. In this paper, we propose an application of Horn-Schunck’s optical flow estimation method in order to obtain the movement field between pairs of seismic images. Optical flow estimation can provide important information about velocity of each image pixel. This way, we show that is possible to catch important displacements between pairs of seismic images separated by a time interval. In this work, each seismic image was deformed through the application of a synthetic field. The results obtained show that this method is able to recover with reasonable precision tiny displacements commonly found in time-lapse seismic data. Introduction The use of time-lapse technologies in order to perform analysis and monitoring of the fluid and pressure in oil and gas producing areas has advanced rapidly in two last decades (Lumley, 2004). These technologies involve the process of taking several seismic surveys separated by a calendar interval, at same site, in order to image and detect important changes in a producing reservoir. If each seismic survey is formed by 3-D data, the extra dimension is calendar time. So, the set of these techniques are often termed “4-D seismic”, and they are quickly becoming a very important engineering reservoir management tool, that can save hundred of million of dollars, when correctly applied (Lumley, 2001). Although 4-D seismic techniques can provide an improved seismic monitoring, residual differences, that are independent of changes in the subsurface geology, may exist in the repeated time-lapse data. These residual differences add noise to the model and consequently impact the effectiveness of the method. So, it is important to ensure seismic repeatability in time-lapse seismic monitoring. A variety of factors are involved in the seismic repeatability study, such as the depth of buried detectors small variations in water table, tides, currents and temperature, ambient noise, transition zone, subsidence, source and geophone positions, source signatures, geometry design, and CMP stack fold distribution. Some of the non-repeatability problems can be solved by the careful deployment of source and receiver positions. However, problems such as those caused by annual near surface variations are more complicated to solve at the acquisition stage. Commonly, these problems can only be solved in the post-processing steps (Zhang and Schmitt, 2006). There are several researches and study cases in seismic literature involving time-lapse techniques application in producing reservoirs. Van Gestel et al. (2008) present their experience in five years of continuous seismic monitoring of Vahal Field, located in the North Sea. The authors show that a combination of permanently installed seismic sensors and highly repeatable acquisition can provide high-quality 4-D images. These images can be used to improve reservoir model and help to plan and reduce risk when drilling new wells. Foster et al. (2008) present an overview of the status of BP’s three oceanbottom cables (OBC) monitoring systems and installation and operation of similar systems at Clair and ACG. OBC systems, in the way that they have been implemented in the three BP deployments, promise highly effective seismic monitoring data, providing both imaging quality and repeatability. Davies et al. (2008) shows that the use of permanent sensors deployed in the wellbore and along the tubing, in the surface production network and in the facilities provide a rich data flow to support advanced well and reservoir management techniques. Arts et al. (2004) present seismic interpretation of time-lapse seismic data provided by monitoring of CO2 injection into a saline aquifer. The authors conclude that the effect of CO2 on the seismic data is large in terms of seismic amplitude and in observed velocity pushdown effects. A new alternative to detect time-lapse seismic effects is proposed by Matos et al. (2004). The authors use self organized maps (SOM) combined with wavelet transform to detect time-lapse changes. Wavelet transform is used in order to detect seismic traces singularities of each time-lapse 3-D cube. Then, these detected objects are classified using the clustering of SOM. The authors also show a successful application of this technique to the Troll West gas province, offshore Norway. Claudino et al. (2008) examine the main effects of permeability barriers on seismic response using fluid flow simulations to generate pressure and saturation fields. The authors have performed several simulations in a simple reservoir model which has vertical and horizontal variations of porosity as well as permeability barriers. The authors use fluid substitution theory, Gassmann and patchy models, and Batzle and Wang’s empirical relationship to model the main seismic parameters, such as acoustic impedance and compressional velocity. Synthetics seismograms and some contrast sections were generated to compare the seismic images prior and