4.5.2.2 Improved Imaging of Reservoir Beneath Gas-Affected Area


Te presence of gas in the overburden (as discussed in Section 4.5.2.1) makes it difficult to map 4D amplitude changes in the reservoir over much of the Valhall crest using tomography- based velocities for imaging. However, significant progress has been made in recent years through the use of Full Waveform Inversion to create an improved velocity model. Figure 4.46 shows an example demonstrating the uplift caused by this step-change improvement in imaging. Te 4D response based on tomographic velocities is shown in Figure 4.46a, where a scattered and broken image in the central portion of the 4D map is visible. Tis is an area with a thick reservoir re-pressurised due to water injection, which should give a very strong 4D response. Gas pockets in the overburden act as lenses which distort the seismic wave-field, and when migration velocities do not represent the actual velocities, the migration process cannot properly reconstruct the wavefield to give a usable image of the subsurface. FWI produces velocity models containing much higher resolution than conventional ray-based reflection tomography. Te 4D image in Figure 4.46b shows a much more coherent 4D signal in the crestal region (dashed circle), because the imaging benefitted from an FWI velocity model (Andorsen et al., 2012). Viewing 3D and 4D data in a vertical section shows that


4D PP data indicates the presence of reservoir where it cannot be interpreted on 3D data. Figure 4.47 illustrates this, comparing a vertical section of LoFS 3D PP and PS data from the 2013–2015 processing with a 2009 4D image using the first available FWI velocities. Te right half of the PP static image is very difficult to interpret reliably, due to degradations in imaging quality caused by gas in the overburden. Te PS data is also affected under the gas, but the quality of the image is quite good because the upgoing S-wave energy is unaffected by gas. If the downgoing energy passes through a region in the overburden with little gas, it is possible to get a good image, as is the case here. Note that to give a good image, the PS migration requires high quality P- and S-wave velocities. Tis was achieved by using FWI to calculate P-wave velocities, followed by joint Vp-Vs inversion to refine the P-wave velocities and define the S-wave velocities. Tese are the first results from Valhall with a good quality 3D static image under the gas cloud. Te bottom image shows that 4D PP signal can be observed where the 3D PP imaging is poor. Tis allowed mapping of the reservoir interval under the gas cloud prior to receipt of the latest PS imaging, when no other image under the gas cloud was available. 4D PP products still give the most reliable prediction of reservoir presence under the gas cloud where imaging is poor. Given the quality of the 3D PS, the Valhall team has embarked on 4D PS processing and is awaiting the data for 2018.


4.5.2.3 4D Seismic Beneath Gas-Affected Area to Update Reservoir Model


As described in the previous example, the quality of LoFS surveys can be strongly impacted by gas in the overburden, but often a robust 4D signal can still be extracted. Interpretation of the 4D signal relies on integrating knowledge of pressure development, production, and injection through


-2100 – -2200 – -2300 – -2400 – -2500 – -2600 – -2700 – -2800 –


-2900 – -2100 – -2200 – -2300 – -2400 – -2500 – -2600 – -2700 – -2800 –


-2900 – -2100 – -2200 – -2300 – -2400 – -2500 – -2600 – -2700 – -2800 – -2900 –


2013 static PP picture


2013 static PS picture


4D 2003 to 2005 (LoFS06-LoFS1) Tor producer Hod producer


Figure 4.47: Comparison of vertical seismic sections. Top – best available static image from LoFS PP data. Middle – best available static image based on PS (converted wave) data. Bottom – 2009 4D using initial FWI results and data from 2003 and 2005, capturing depletion prior to any water injection. The right half of the static PP section is very difficult to interpret with any confidence due to degradation of imaging related to gas in the overburden. The PS static image remains reasonably good under the zone where gas affects the PP data. The 4D AI (acoustic impedance) image shows red events which indicate an increase in amplitude impedance (reservoir hardening) due to depletion. Note that there is no 4D signal associated with the right-most (blue) well because it was drilled after the seismic data were acquired (courtesy of the Valhall JV, Aker-BP and Hess)


time (including water break-through in production wells), dynamic modelling of the reservoir, and from generating synthetic 4D seismic based on the dynamic reservoir modelling and the rock properties model. Tis is an iterative and interdisciplinary process. Figure 4.48 illustrates an example of this type of


integration from the central crest. It shows the reservoir thickness from the reservoir model, changes in water saturation (Sw), pressure (P), and gas saturation (Sg), the modelled 4D seismic response (Syn AI), and the actual 4D response (Seis AI). Te time period modelled is from 2005 (LoFS6), which correlates to the onset of water injection, to 2011 (LoFS14). In general, the extent and form of the modelled 4D response correlates best with the modelled decrease in Sg (gas going back into solution) due to a pressure increase. However, changes in Sw, Sg and pressure are all affecting the rock properties, complicating the 4D response. Te actual 4D signal is shown on the bottom right. Te modelled 4D response differs from the actual 4D response, with a dominant


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