Using Crosswell Data To Enhance History Matching

Abstract

One of the most challenging tasks in the oil industry is the production of reliable reservoir forecast models. Due to different sources of uncertainties in the numerical models and inputs, reservoir simulations are often only crude approximations of the reality. This problem is mitigated by conditioning the model with data through data assimilation, a process known in the oil industry as history matching. Several recent advances are being used to improve history matching reliability, notably the use of time-lapse data and advanced data assimilation techniques. One of the most promising data assimilation techniques employed in the industry is the ensemble Kalman filter (EnKF) because of its ability to deal with non-linear models at reasonable computational cost. In this paper we study the use of crosswell seismic data as an alternative to 4D seismic surveys in areas where it is not possible to re-shoot seismic. A synthetic reservoir model is used in a history matching study designed better estimate porosity and permeability distributions and improve the quality of the model to predict future field performance.This study is divided in three parts: First, the use of production data only is evaluated (baseline for benchmark). Second, the benefits of using production and 4D seismic data are assessed. Finally, a new conceptual idea is proposed to obtain timelapse information for history matching. The use of crosswell time-lapse seismic tomography to map velocities in the interwell region is demonstrated as a potential tool to ensure survey reproducibility and low acquisition cost when compared with fullscale surface surveys. Our numerical simulations show that the proposed method provides promising history matching results leading to similar estimation error reductions when compared with conventional history matched surface seismic data.

Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

“…The main assumptions of Biot's theory are that the underlying rocks are isotropic and that all minerals making up the rock structure have the same bulk and shear moduli (Biot 1956). Although Gassmann's equations were widely used because of their simplicity and correspond to the Biot velocities in the low-frequency limit, for high-frequency seismic waves, as Hoteit and Ravanelli 2014). With the full acoustic-wave propagation solvers, this may lead to significantly distorted seismic recordings and hence, misrepresentation of the formation structure.…”

History Matching of Electromagnetically Heated Reservoirs Incorporating Full-Wavefield Seismic and Electromagnetic Imaging

“…The seismic survey module consists of a full-waveform 2D acousticwave-propagation solver and a Biot petrophysical transformation (Russell et al 2003). The Biot petrophysical transformation calculates the velocity and density profile of the formation structure with Biot theory, and was used in reservoir history matching (Russell et al 2003;Hoteit and Ravanelli 2014). It deals with the propagation properties of acoustic waves in porous media and is based on the assumption that the wavelength is large compared with the size of the macroscopic elementary volume, assuming a linear strain tensor and isotropic rock matrix.…”

A Sparse Bayesian Imaging Technique for Efficient Recovery of Reservoir Channels With Time-Lapse Seismic Measurements

“…the geological model) from the dynamic fluid flow component, which should provide information to help recovering the geological structures [30,33]. The first successful use of 4D seismic under an EnKF framework was presented by Skjervheim et al in [34] and more recently gained momentum in helping to monitor the fluid flow movement in the reservoir [35,36,37,38].…”