Controlled Source EM to Monitor Steam Injection in the Ratqa Heavy Oil Reservoir

2018 ◽  
Author(s):  
Nestor Cuevas ◽  
Adel Hassan El-Emam ◽  
Jarrah Al-Jenaie ◽  
Mohamed Hafez ◽  
Federico Ceci ◽  
...  
Keyword(s):  
Heavy Oil ◽  
Steam Injection ◽  
Oil Reservoir ◽  
Controlled Source ◽  
Heavy Oil Reservoir

A New Method of Calculating Water Invasion for Heavy Oil Reservoir by Steam Injection

2007 ◽  
Author(s):  
Hong'en Dou ◽  
Changchun Chen ◽  
Yuwen Chang ◽  
Xiaolin Wang ◽  
Fenglan Wang ◽  
...  
Keyword(s):  
Heavy Oil ◽  
Steam Injection ◽  
New Method ◽  
Oil Reservoir ◽  
Heavy Oil Reservoir

Seismic characterization of heavy oil reservoir during thermal production: A case study

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. B13-B27 ◽  
Author(s):  
Hemin Yuan ◽  
De-Hua Han ◽  
Weimin Zhang
Keyword(s):  
Heavy Oil ◽  
Rock Physics ◽  
Time Lapse ◽  
Steam Injection ◽  
Oil Reservoirs ◽  
Inversion Method ◽  
Oil Reservoir ◽  
Steam Chamber ◽  
Heavy Oil Reservoirs ◽  
Heavy Oil Reservoir

Heavy oil reservoirs are important alternative energy resources to conventional oil and gas reservoirs. However, due to the high viscosity, most production methods of heavy oil reservoirs involve thermal production. Heavy oil reservoirs’ properties change dramatically during thermal production because the viscosity drops drastically with increasing temperature. Moreover, the velocity and density also decrease after steam injection, leading to a longer traveltime of seismic velocities and low impedance of the steam chamber zone. These changes of properties can act as indicators of the steam chamber and can be detected through the time-lapse inversion method. We first establish the rock-physics relationship between oil sands’ impedance and temperature on the basis of our previous laboratory work. Then, we perform the forward modeling of the heavy oil reservoir with the steam chamber to demonstrate the influence of steam injection on seismic profiles. Then, we develop a modified-Cauchy prior-distribution-based time-lapse inversion method and perform a 2D model test. The inversion method is then applied on the real field data, and the results are analyzed. By combining the inverted impedance and rock-physics relation between impedance and temperature, the temperature distribution map is obtained, which can work as an indicator of steam chamber. Finally, an empirical relation between impedance and velocity is established, and velocity is derived from the impedance.

Experimental Research on Hot Water Flooding of Different Rhythm Heavy Oil Reservoir after the Steam Injection

2012 ◽  
Vol 550-553 ◽  
pp. 2878-2882 ◽  
Author(s):  
Ping Yuan Gai ◽  
Fang Hao Yin ◽  
Ting Ting Hao ◽  
Zhong Ping Zhang
Keyword(s):  
Oil Recovery ◽  
Heavy Oil ◽  
Physical Simulation ◽  
Steam Injection ◽  
Hot Water ◽  
Water Flooding ◽  
Oil Reservoir ◽  
Steam Flooding ◽  
Heavy Oil Reservoir ◽  
Swept Volume

Based on the issue of enhancing oil recovery of heavy oil reservoir after steam injection, this paper studied the development characteristics of hot water flooding in different rhythm (positive rhythm, anti-rhythm, complex rhythm) reservoir after steam drive by means of physical simulation. The research shows that the positive rhythm reservoir has a large swept volume with steam flooding under the influence of steam overlay and steam channeling. Anti-rhythm reservoir has a large swept volume with hot water flooding, because hot water firstly flows along the high permeability region in upper part of the reservoir, in the process of displacement, hot water migrates to the bottom of reservoir successively for its higher density.

Sensitivity of Steamflood Model Results to Grid and Timestep Sizes

1984 ◽  
Vol 24 (01) ◽  
pp. 65-74 ◽  
Author(s):  
Jamal Hussein Abou-Kassem ◽  
Khalid Aziz
Keyword(s):  
Heavy Oil ◽  
Size Effects ◽  
Truncation Error ◽  
Injection Pressure ◽  
Steam Injection ◽  
Sensitivity Study ◽  
Grid Size ◽  
Oil Reservoir ◽  
Fully Implicit ◽  
Heavy Oil Reservoir

Abstract Numerical simulation of complex processes in oil reservoirs has become a standard tool. The grid size and timestep sensitivity of a simulator are of prime concern in reaching the correct conclusions in any study. This paper presents an analysis of the sensitivity to timestep and grid size of a one-dimensional (1D) and two-dimensional (2D) compositional multiphase steamflood model used to simulate a heavy-oil reservoir. The behavior of primary variables before breakthrough in the 1D and 2D cases is presented for clearer understanding of steamflooding heavy-oil reservoirs. The peculiar features exhibited by primary variables of the production and injection blocks for the 1D reservoir plus timestep and grid-size effects on primary variables for 2D cases studied are discussed. Sensitivity studies of grid and timestep size are meaningful only if each is carried out while the other variable has minimum truncation error. The recovery performance parameters are less sensitive to timestep size than to grid size. They are also less sensitive in the 2D runs than in the 1D runs. The time/pore-volume-injected (PVI) relationship is very sensitive to grid size, and to a lesser extent, to timestep size. Introduction Numerical dispersion is particularly important in simulating multiphase flow, miscible displacement, and compositional phenomena. Settari recommends that detailed study be carried out on grid- and timestep-size effects. A grid-size sensitivity study is recommended when a reservoir is simulated to define the necessary grid size used. Such a study requires a series of simulation runs with increasing or decreasing grid definition. When simulators with fully implicit formulation are used, where large time steps are possible, the time truncation error also can become important. Therefore, a timestep sensitivity study for these simulators is also necessary."Sensitivity analysis" refers to the sensitivity of the primary variables and recovery performances to grid and timestep size. A review of recent literature reveals that grid and timestep effects have not been studied on all primary variables for 1D simulations and are lacking for 2- or 3D simulations. Sensitivity analyses for both 1- and 2D simulation of a heavy-oil reservoir along with a study of the behavior of primary variables in steamflooding are presented. Simulator and Data Used The simulator used in this study was developed by Abou-Kassem. A brief description of the simulator is given in Ref. 9. It is a fully implicit, compositional, three-phase steamflood model. The model employs a sophisticated well model and a nine-point finite-difference scheme in two dimensions only. It can be operated in 1- and 2D modes with the choice of block-centered or point-distributed grid. In this paper only results of a block-centered grid with gas hysteresis and with no heat loss to surrounding formations are presented. The reservoir is represented by a one-fourth five-spot flood pattern with dimensions of 137 × 137 × 63 ft [41.76 × 41.76 × 19.2 m]. The permeability and porosity are 4 darcies and 0.38, respectively. The reservoir is initially saturated with 18 % water and 82 % heavy oil composed of 70 % nonvolatile oil component and 30 % methane. The nominal mobility ratio is 285,000, which corresponds to an effective mobility ratio of about 10,000. The Appendix provides more detailed data. Steam of 0.70 quality at an injection pressure of 1,000 psia [6.9 MPa] was injected into the reservoir having an initial pressure and temperature of 554 psia [3.9 MPa] and 60F [288.7K], respectively. The maximum steam injection rate was 883 cu ft/D [25 m3/d] cold water equivalent (CWE). The production well was put on "deliverability" control with a bottomhole pressure (BHP) of 400 psk [2.8 MPa]. The reservoir is simulated with a uniform grid (with square block for 2D). Results and Discussion Results of the simulator used in this study were compared with results obtained from a commercial steam model in 1D and 2D modes. Excellent agreement was obtained when the simulator was run with the five-point finite-difference formulation. The 2D results presented next are for a diagonal grid with the nine-point difference scheme. Behavior of Primary Variables in Steamflood Simulation. Primary Variables of Injection Well Block (1-D Simulation). The behavior of the primary variables associated with the injection block as a function of PVI is shown in Fig. 1. As steam injection begins, the pressure increases first moderately then very rapidly because the system has been compressed and all fluids are almost immobile. The pressure of the injection block is slightly less than the maximum injection pressure. SPEJ P. 65^

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