Seismic History Matching of Fluid Fronts Using the Ensemble Kalman Filter

Abstract

Time-lapse seismic data provide information on the dynamics of multiphase reservoir fluid flow in places where no production data from wells are available. This information, in principle, could be used to estimate unknown reservoir properties. However, the amount, resolution, and character of the data have long posed significant challenges for quantitative use in assisted-historymatching workflows. Previous studies, therefore, have generally investigated methods for updating single models with reduced parameter-uncertainty space. Recent developments in ensemblebased history-matching methods have shown the feasibility of multimodel history and matching of production data while maintaining a full uncertainty description. Here, we introduce a robust and flexible reparameterization for interpreted fluid fronts or seismic attribute isolines that extends these developments to seismic history matching. The seismic data set is reparameterized, in terms of arrival times, at observed front positions, thereby significantly reducing the number of data while retaining essential information. A simple 1D example is used to introduce the concepts of the approach. A synthetic 3D example, with spatial complexity that is typical for many waterfloods, is examined in detail. History-matching cases based on both separate and combined use of production and seismic data are examined. It is shown that consistent multimodel history matches can be obtained without the need for reduction of the parameter space or for localization of the impact of observations. The quality of forecasts based on the history-matched models is evaluated by simulating both expected production and saturation changes throughout the field for a fixed operating strategy. It is shown that bias and uncertainty in the forecasts of production both at existing wells and in the flooded area are reduced considerably when both production and seismic data are incorporated. The proposed workflow, therefore, enables better decisions on field developments that require optimal placement of infill wells.

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

“…By repeating seismic surveys after a period of production it is often possible to identify the fronts between water or gas displacing oil, and this information can help to drastically increase the quality of the update; see e.g., Skjervheim (2007), Trani et al (2012), Jin et al (2012), Emerick and Reynolds (2013) and Hadavand and Deutsch (2016). Also, the increasing use of different geophysical measurements such as gravity or electromagnetic surveys can be of help to obtain a better picture of the subsurface fluid distribution, and, through inversion, of the reservoir model parameters; see e.g., Glegola et al (2012) and Katterbauer et al (2016).…”

EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

“…In contrast to the work of Trani et al (2013), where seismic data were assumed to provide information about saturation changes in time, we included seismic and electromagnetic measurements via petrophysical transformations directly into the observation operator of the tested EnKFs. As stated above, the approach presented here is to incorporate time lapse seismic data, which are represented by the change either in bulk modulus, impedance, velocity, Poisson impedance, or time lapse electromagnetic data, represented by the change in conductivity for several different models, into the observation operator.…”

“…Reservoir history matching has traditionally been a manual task, where experienced engineers fine tune parameters to match the simulated trajectories with the real ones. Significant progress has been made in the last decade in the automatization of this process using ensemble-based Kalman Filters (EnKFs) (e.g., Aanonsen et al, 2009;Leeuwenburgh et al, 2011;Luo and Hoteit, 2011;Phale and Oliver, 2011;Trani et al, 2013). EnKFs are sequential history matching techniques that use an ensemble of model states to represent the error statistics of the model estimate.…”

Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

“…The 4D seismic gained prominence in monitoring the changes within a reservoir, with many studies using them for reservoir history-matching purposes (Skjervheim et al 2007; Sedighi-Dehkordi and Stephen 2010; Leeuwenburgh et al 2011;Kazemi et al 2011;Trani et al 2013). Skjervheim et al (2007) successfully incorporated inverted time-lapse seismic data and production data into the EnKF for reservoir model updating, improving the permeability estimate for synthetic and real field cases of the North Sea.…”