Integrating Geomechanics and Geophysics for Reservoir Seismic Monitoring Feasibility Studies

Abstract

Seismic measurements acquired at different stages in the life of a reservoir can monitor the fluid distribution over production time. Changes in saturation, pore pressure and stresses, induced by reservoir production may influence the process of wave propagation in rocks. The variations in mean effective stresses, due to changes in mean stress or /and pore pressure, are not always integrated in a proper manner. We present here a methodology to evaluate what is the contribution of a geomechanical approach on the computation of seismic velocities. This methodology has been used for the monitoring of an underground gas storage site of Gaz de France, the French gas Supply Company. Successful results illustrate the importance of integrating geomechanics with geophysics to validate real sonic data from DSI. Introduction Seismic monitoring (time-lapse or 4D) has emerged as one of the most important technical developments in the oil and gas industry for this decade. This technique has the potential to significantly enhance recovery and optimize exploitation schemes in existing and new fields. It aims at monitoring -by repeated VSP, 2D or 3D seismic surveys- seismic changes, velocity and density, related to fluid, stresses and temperature changes during the production of a field. Changes in density and velocity result in impedances changes which, under favorable conditions, can be detected in seismic data. The probability of success of the technique heavily depends on many factors, like reservoir parameters (depth, rock and fluid properties, pressure, …), nature of the recovery processes and the repeatability of the different seismic surveys1. A careful feasibility study on the field of interest, coupled with a clear reservoir objective, is required to give a realistic estimate of what seismic monitoring can provide for reservoir management. The Céré-la-Ronde underground gas storage reservoir, in the Paris Basin, is used as a test site to study and improve reservoir seismic monitoring methods (Fig. 1). It is a water-bearing sandstone reservoir in a faulted anticline structure. The depth of reservoir is about 900 meters and its thickness is about 25 meters, at the structure top (Fig. 2). Regarding seismic monitoring, the site presents favorable characteristics -shallow reservoir and gas injection process1-, and unfavorable ones -low repeatability due to unpredictable statics-. The different repetitive acquired data (DSI, VSP, walk-away and 2D seismic) allow so far a qualitative seismic interpretation of the gas bubble location, by studying fluid saturation influence2. However, between 1994 and 1997, two DSI logs show subtle differences on Vp velocity not explained by saturation variations only. Changes in pore pressure and stresses also influence the computation of seismic velocities. Hence, using geomechanical modeling, we want to evaluate in a quantitative way, how the gas reservoir exploitation influences the seismic measurements. Several previous studies have shown the interest of using both fluid saturation and pore pressure to interpret time-lapse seismic data3,4. In all these works, when the influence of mean effective stress on seismic velocities is studied, only pore pressure is considered and mean total stress is seen as constant. Usually, stresses evolve during reservoir exploitation. In our approach, using geomechanical modeling, we will consider variations in the mean effective stresses, induced by changes in both the mean total stresses and pore pressure distribution. This paper presents a methodology developed in order to integrate geomechanical modeling in the calculation of seismic velocities. This implies to combine geomechanics with geophysics. The implementation of this method is composed of three steps. In step1, in order to take into account multiphasique fluid flow, pore pressure and saturations are computed by a reservoir simulator. Then, the computed pore pressure is used as a load in the geomechanical modeling, (step2). In step3, the results of the geomechanical modeling (mean effective stresses) are used to compute the drained bulk modulus (Kd) and the shear modulus (µ), using rock physics.

Reservoir Monitoring

“…The resulting reservoir model constitutes the best possible input to determine whether subsequent 4D monitoring is feasible or not (Khan et al, 2000;Vidal et al, 2000). It is usually conducted for the given reservoir using measured rock, fluid properties, and reservoir simulation model.…”

An Intelligence Approach for Porosity and Permeability Prediction of Oil Reservoirs using Seismic Data

“…In the original Hertz-Mindlin theory n is identical to 3. Some laboratory measurements of samples proposed a larger number for n. Vidal [11] discovered n = 5.6 for Pwaves and n = 3.8 for shear waves for gas sands, while Landrø [12] employed n = 5 for oil sands. We use n = 5 in this study.…”

Porosity and Permeability Estimation by Gradient-Based History Matching Using Time-Lapse Seismic Data

“…Vidal et al 30 found n=5.6 for the P-wave and n=3.8 for the S-wave in gas sands, while Landrø 31 used n=5 for oil sands. This correction is used for developing forward modeling in this study (n=5 instead n=3).…”