Improper planning and execution of deepwater drilling programs can lead to high costs and unsafe conditions. Proper well planning requires reliable estimates of the expected pore fluid pressure and formation strength prior to drilling. Such pressure predictions are based on integrated seismic and offset well data. A new, rock model-based approach especially suited for deepwater pore pressure imaging is introduced here and applied in an example of a deepwater Gulf of Mexico well. P- and S- velocities were determined both at an offset well and for the future drilling location, using prestack seismic full waveform inversion. Both predicted velocities were later verified with log measurements. Using the new model, a significant pore pressure increase at depth was predicted before drilling the well and verified while drilling (Figure 1). For the entire well, the predicted and measured pore pressure gradients agree within half a pound per gallon equivalent mudweight (Figure 1). The shear velocity, and the extracted shear modulus, proved to be excellent indicators of low effective stresses, corresponding to overpressured formations (Figure 2). Introduction It has been common practice to predict pore pressure before drilling from conventional seismic stacking velocities with a normal compaction trend analysis using, for example, the well-known Eaton approach (Eaton, 1972). Velocities that appear to be slower than the ‘normal velocities’ are indicative of overpressure, which then is quantified using an empirical equation. However, there are several problems with this approach. First, conventional seismic stacking velocities are usually unsuitable for pressure prediction since they are not "rock or propagation velocities" (Al-Chalabi, 1994). Second, these velocities lack resolution in depth. Third, in a deepwater environment, sediment loading often has been so fast that pressures in these sediments are above hydrostatic (geopressured) right below the mud line - unlike, for example, on the continental shelf of the Gulf of Mexico (Dutta, 1997). This prevents development of a normal compaction trend, thus invalidating the entire approach in the deepwater. Our new approach is trendline independent and uses a deepwater rock model for geopressure analysis. The model (or approach) is based on several seismic attributes, such as velocities and amplitudes and is calibrated with offset well information. Pore pressure is calculated as the difference between overburden stress and effective stress. The effective stress affects the grain-to-grain contacts of clastic, sedimentary rock, and consequently, the velocities of seismic waves propagating through such rock (Domenico, 1984; Dutta, 1997). The rock model has various components: relations between porosity, lithology and velocity, clay dehydration, and transformations relating both density and Poisson's ratios of the sediments to effective stresses acting on the matrix framework. The key inputs that drive the rock model are velocities (P and S) obtained from a variety of velocity tools. Iterative velocity calibration and interpretation are two essential steps in the prediction process to ensure that the velocity fields are within the realm of expected rock or propagation velocities. In the following study, we demonstrate how the P- and S- velocities used in a Gulf of Mexico example were derived using prestack waveform inversion and we describe the rock model in more detail.
A pilot study was initiated to evaluate the feasibility of using legacy 3-D seismic time-lapse analysis as a reservoir monitoring tool to assist planning future development in a shallow oil and gas field in the Gulf of Mexico. The reservoir selected for initial evaluation was the shallowest of a series of stacked oil and gas pays. This choice was based on seismic data quality and the desire to eliminate any possible effects of production in overlying reservoirs.The target reservoir produces gas from a faulted anticlinal trap at a depth of about 3000 ft, is normally pressured, and exhibits a strong water drive. The reservoir has been produced by three wells, two of which are no longer producing gas due to high water production.Two 3-D seismic surveys have been acquired since initial production-one in 1987 and the other in 1995. During the interim between surveys, approximately 26.6 billion ft 3 of gas was produced. Maps based on the 3-D data show good structural conformance of seismic amplitude with known hydrocarbon/water contacts, and indicate potential drilling locations in undrilled fault blocks updip from the depleted wells. The technique developed in this study uses the two existing (legacy) 3-D data sets in conjunction with well logs and production data to provide spatial constraints on estimates of produced and remaining reserves.Fluid substitution study. The first phase of this study involved modeling the expected acoustic response of the reservoir to simulate fluid saturation changes. Initial efforts using a uniform or "pure saturation" Gassmann-based fluid substitution model did not adequately predict the observed seismic response. As a result, we used a "patchy saturation" model to better describe observable differences in seismic data. This model predicted an acoustic impedance increase of approximately 10% in the swept zone (30% gas being replaced by water). Tuning analysis used a wedge model with an assumed central frequency of 30 Hz in the seismic wavelet (0-60 Hz). The corresponding tuning thickness was determined by (1) where V is the velocity of the layer and f c is the central frequency of the seismic data assuming the central frequency is dominant. However, two potential sources of error are possible when applying this relation to legacy seismic data. The variation of computed tuning thickness may result from variation in seismic velocity caused by production-related fluid substitution or from variation in frequencies between data sets.We will use the model in Figure 1, a wedge with thickness varying from 0-150 ft and a gas cap, to illustrate this ambiguity. Water saturation in the gas cap was systematically increased in successive modeling runs. Corresponding values of acoustic impedance and amplitude were calculated assuming a patchy saturation distribution. These data are listed in Table 1. The results of these model runs are shown in Figure 2 in which seismic ampli-278 THE LEADING EDGE MARCH 2001 MARCH 2001 THE LEADING EDGE
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.