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Synonym: = Volatile/Black Oil Reservoir Flow @model = Muskat - Leverett equation


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Definition



Mathematical model of Modified Black Oil fluid ( = Volatile Oil ) reservoir flow predicts the temperature, pressure and flow speed distribution in reservoir with account for:

  • available historical data on surface flowrates and/or bottom hole pressure

  • available 3D geological model 

  • PVT and SCAL model

  • specific wellbore designs

  • gravitational forces

  • heat propagation

  • adiabatic and Jole-Thomson heat effects 


The Black Oil flow is specific type of the Volatile Oil flow with  R_v=0.


Foundation



Consider Modified Black Oil fluid @model consisting of three chemical components C = \{ W, \, O, \, G \} which may exists in three phases f = \{ w, \, o, \, g \}


The driving equations of Modified Black Oil Reservoir Flow Grid Computation @model are:


1
\frac{dm^*_C}{dt} \, = \, \, \mbox{const}


mass conservation of m^*_W, \, m^*_O, \, m^*_G – stock tank mass of the chemical components C = \{ W, \, O, \, G \}

2
(1) \bar u_f = -  k_p \cdot \frac{k_{rf}}{\mu_f} \cdot \big( \hat k * \bar \nabla} (p + p_{cf}) - \rho_f \cdot \hat k * \bar g \big)\, \quad f = \{ w, \, o, \, g \}


Darcy transport equation dor the velocity \bar u_f of three phases: f = \{ w, \, o, \, g \}

3
(2) \phi = \phi_0 \cdot \exp(c_\phi \cdot (p-p_0))


Pore compressibility equation on reservoir porosity \phi(p)

4
(3) \rho_f = \rho_f(T,p) \, , \quad \mu_f = \mu_f(T,p) \, , \quad R_s = R_s(T,p) \, , \quad \mu_f = \mu_f(T,p)


Equation of state

5
(4) (\rho \,c_{pt})_p \frac{\partial T}{\partial t}   - \ \phi \sum_{f = \{w,o,g \}} \rho_f \ c_{pf} \ \eta_{sf} \ \frac{\partial p_f}{\partial t}   + \bigg( \sum_{f = \{w,o,g \}} \rho_f \ c_{pf} \ \epsilon_f \ \mathbf{u}_f \bigg) \nabla p   + \bigg( \sum_{f = \{w,o,g \}} \rho_f \ c_{pf} \ \mathbf{u}_f \bigg) \ \nabla T   - \nabla (\lambda_t \nabla T) = \rho^{\downarrow} ({\bf r}) \, c^{\downarrow} ({\bf r}) \, T^{\downarrow} ({\bf r}) \, q^{\downarrow}({\bf r})\, \delta({\bf r})


Heat balance and transfer equation


Mathematical Model – Integral Format



(5) \frac{\partial m_W}{\partial t} + \int\rho_{Ww} \cdot\, \bar u_w \, d \bar \Sigma = \frac{d m^*_W}{dt}
(6) \frac{\partial m_O}{\partial t} + \int \left( \rho_{Oo} \cdot \, \bar u_o + \rho_{Og} \cdot \, \bar u_g \right) d \bar \Sigma = \frac{d m^*_O}{dt}

(7) \frac{\partial m_G}{\partial t} + \int \left( \rho_{Go} \cdot \, \bar u_o + \rho_{Gg} \cdot \, \bar u_g \right) d \bar \Sigma = \frac{d m^*_G}{dt}


(8) \rho_{Ww} = \frac{m_W}{V_w} = \frac{m_W}{V_W} \cdot \frac{V_W}{V_w} = \frac{\mathring \rho_W}{B_w}
(9) \rho_{Oo} = \frac{m_{Oo}}{V_o} = \frac{m_{Oo}}{V_O} \cdot \frac{V_O}{V_o} = \frac{\mathring \rho_O}{B_o}
(10) \rho_{Og} = \frac{m_{Og}}{V_g} = \frac{m_{Og}}{V_{Og}} \cdot \frac{V_{Og}}{V_G} \cdot \frac{V_G}{V_g} = \frac{\mathring \rho_O \cdot R_v}{B_g}
(11) \rho_{Go} = \frac{m_{Go}}{V_o} = \frac{m_{Go}}{V_{Go}} \cdot \frac{V_{Go}}{V_O} \cdot \frac{V_O}{V_o} = \frac{\mathring \rho_G \cdot R_s}{B_o}
(12) \rho_{Gg} = \frac{m_{Gg}}{V_g} = \frac{m_{Gg}}{V_G} \cdot \frac{V_G}{V_g} = \frac{\mathring \rho_G}{B_g}


(13) \frac{\partial m_W}{\partial t} + \mathring \rho_W \int \frac{1}{B_w} \, \bar u_w \, d \bar \Sigma = \frac{d m^*_W}{dt}

(14) \frac{\partial m_O}{\partial t} + \mathring \rho_O \int \left( \frac{1}{B_o} \cdot \, \bar u_o + \frac{R_v}{B_g} \cdot \, \bar u_g \right) d \bar \Sigma = \frac{d m^*_O}{dt}
(15) \frac{\partial m_G}{\partial t} + \mathring \rho_G \int \left( \frac{R_s}{B_o} \cdot \, \bar u_o + \frac{1}{B_g} \cdot \, \bar u_g \right) d \bar \Sigma = \frac{d m^*_G}{dt}


(16) V_W = \mathring \rho_W^{-1} \cdot m_W
(17) V_O = \mathring \rho_O^{-1} \cdot m_O
(18) V_G = \mathring \rho_G^{-1} \cdot m_G


(19) q_W = \mathring \rho_W^{-1} \cdot \frac{d m^*_W}{dt}

(20) q_O = \mathring \rho_O^{-1} \cdot \frac{d m^*_O}{dt}

(21) q_G = \mathring \rho_G^{-1} \cdot \frac{d m^*_G}{dt}


(22) \frac{\partial V_W}{\partial t} + \int \frac{1}{B_w} \, \bar u_w \, d \bar \Sigma = q_W
(23) \frac{\partial V_O}{\partial t} + \int \left( \frac{1}{B_o} \cdot \, \bar u_o + \frac{R_v}{B_g} \cdot \, \bar u_g \right) d \bar \Sigma = q_O
(24) \frac{\partial V_G}{\partial t} + \int \left( \frac{R_s}{B_o} \cdot \, \bar u_o + \frac{1}{B_g} \cdot \, \bar u_g \right) d \bar \Sigma = q_G


(25) V_w = B_w \cdot V_W
(26) V_o =\frac{B_o}{1-R_s \, R_v} \cdot (V_O - R_v \, V_G)
(27) V_g =\frac{B_g}{1-R_s \, R_v} \cdot (V_G - R_s \, V_O)
(28) V_\phi = V_w + V_o + V_g
(29) s_w = \frac{V_w}{V_\phi}
(30) s_o = \frac{V_o}{V_\phi}
(31) s_g = \frac{V_g}{V_\phi}
(32) s_w + s_o + s_g = 1
(33) V_\phi = V_w + V_o + V_g = B_w \cdot V_W + \frac{B_o - R_s \cdot B_g}{1-R_s \, R_v} \cdot V_O + \frac{B_g - R_v \cdot B_o}{1-R_s \, R_v} \cdot V_G
(34) V_\phi = V_w + V_o + V_g = B_w \cdot V_W + \frac{B_o - R_s \cdot B_g}{1-R_s \, R_v} \cdot V_O + \frac{B_g - R_v \cdot B_o}{1-R_s \, R_v} \cdot V_G




(35) \phi = \phi_0 \cdot \exp \big( c_\phi \cdot (p-p_0) \big)
(36) \phi = \frac{V_\phi}{V} = \frac{V_w}{V} + \frac{V_o}{V} + \frac{V_g}{V}



(37) B_w \cdot \frac{V_W}{V_{\phi0}} + \frac{B_o - R_s \cdot B_g}{1-R_s \, R_v} \cdot \frac{V_O}{V_{\phi0}} + \frac{B_g - R_v \cdot B_o}{1-R_s \, R_v} \cdot \frac{V_G}{V_{\phi0}} = \exp \big( c_\phi \cdot (p-p_0) \big), \quad V_{\phi0} = V \cdot \phi_0
(38) \tilde B_w = B_w
(39) \tilde B_o = \frac{B_o - R_s \cdot B_g}{1-R_s \, R_v}
(40) \tilde B_g = \frac{B_g - R_v \cdot B_o}{1-R_s \, R_v}


(41) \tilde B_w \cdot \frac{V_W}{V_{\phi0}} + \tilde B_o \cdot \frac{V_O}{V_{\phi0}} + \tilde B_g \cdot \frac{V_G}{V_{\phi0}} = \exp \big( c_\phi \cdot (p-p_0) \big), \quad V_{\phi0} = V \cdot \phi_0




(42) \bar u_w = -  k_p \cdot \frac{k_{rw}}{\mu_w} \cdot \hat k * \big( \bar \nabla} p_w - \rho_w \cdot \bar g \big)
(43) \bar u_o = -  k_p \cdot \frac{k_{ro}}{\mu_o} \cdot \hat k * \big( \bar \nabla p_o - \rho_o \cdot   \bar g \big)
(44) \bar u_g = -  k_p \cdot \frac{k_{rg}}{\mu_g} \cdot \hat k * \big( \bar \nabla p_g - \rho_g \cdot   \bar g \big)
(45) k_p = \exp \big[ c_k \, (\,p - p_{\mathrm{ref}}\,) \big]

Given arbitrary coordinate system: \bold e = \{ \, \bar e_1, \, \bar e_2, \, \bar e_3 \, \}:

(46) \hat k * \bar v =   \bar e_1 \cdot (k_{11} \, v_1 + k_{12} \, v_2 + k_{13} \, v_3)   + \bar e_2 \cdot (k_{21} \, v_1 + k_{22} \, v_2 + k_{23} \, v_3)  + \bar e_3 \cdot (k_{31} \, v_1 + k_{32} \, v_2 + k_{33} \, v_3)

(47) \hat k * \bar \nabla =   \bar e_1 \, (k_{11} \, \partial_1 + k_{12} \, \partial_2 + k_{13} \, \partial_3)   + \bar e_2 \,(k_{21} \, \partial_2 + k_{22} \, \partial_2 + k_{23} \, \partial_3)  + \bar e_3 \, (k_{31} \, \partial_1 + k_{32} \, \partial_2 + k_{33} \, \partial_3)

(48) \hat k * \bar g =   \bar e_1 \, (k_{11} \, g_1 + k_{12} \, g_2 + k_{13} \, g_3)   + \bar e_2 \,(k_{21} \, g_1 + k_{22} \, g_2 + k_{23} \, g_3)  + \bar e_3 \, (k_{31} \, g_1 + k_{32} \, g_2 + k_{33} \, g_3)


(49) \rho_w = \frac{ \mathring \rho_W}{B_w}
(50) \rho_o = \frac{ \mathring \rho_O + \mathring \rho_G \cdot R_s}{B_o}
(51) \rho_g = \frac{ \mathring \rho_G + \mathring \rho_O \cdot R_v}{B_g}




(52) \bar u_w = -  k_p \cdot \frac{k_{rw}}{\mu_w} \cdot \big( \hat k * \bar \nabla} p_w - \rho_w \cdot \hat k * \bar g \big)
(53) \bar u_o = -  k_p \cdot \frac{k_{ro}}{\mu_o} \cdot \big( \hat k * \bar \nabla p_o - \rho_o \cdot  \hat k * \bar g \big)
(54) \bar u_g = -  k_p \cdot \frac{k_{rg}}{\mu_g} \cdot \big( \hat k * \bar \nabla p_g - \rho_g \cdot  \hat k * \bar g \big)





(55) \bar u_w = -  k_p \cdot \frac{k_{rw}}{\mu_w} \cdot \big( \hat k * \bar \nabla} (p + p_{cw}) - \rho_w \cdot \hat k * \bar g \big)
(56) \bar u_o = -  k_p \cdot \frac{k_{ro}}{\mu_o} \cdot \big( \hat k * \bar \nabla (p + p_{co}) - \rho_o \cdot  \hat k * \bar g \big)
(57) \bar u_g = -  k_p \cdot \frac{k_{rg}}{\mu_g} \cdot \big( \hat k * \bar \nabla (p + p_{cg}) - \rho_g \cdot  \hat k * \bar g \big)


(58) p_w = p + p_{cw}, \quad p_{cw} = \frac{1}{3} \cdot ( -2 \cdot p_{cow} + p_{cog} )
(59) p_o = p + p_{co}, \quad p_{co} = \frac{1}{3} \cdot (p_{cow} + p_{cog})
(60) p_g = p + p_{cg}, \quad p_{cg} = \frac{1}{3} \cdot (p_{cow} - 2 \cdot p_{cog} )
(61) p = \frac{1}{3} \left( p_o + p_g + p_w \right)
(62) \dot p_{cw} = \frac{dp_{cw}}{ds_w}
(63) \dot p_{co} = \frac{dp_{co}}{ds_o}
(64) \dot p_{cg} = \frac{dp_{cg}}{ds_g}









Mathematical Model – Divergence Format



The Volatile Oil flow dynamics is defined by the following set of 3D equations:

(65) \partial_t \bigg [ \phi \ \bigg ( \frac{s_w}{B_w} \bigg ) \bigg ] + \nabla \bigg ( \frac{1}{B_w} \ \mathbf{u}_w \bigg ) = q_W (\mathbf{r})
(66) \partial_t \bigg [ \phi \ \bigg ( \frac{s_o}{B_o} + \frac{R_v \ s_g} {B_g} \bigg ) \bigg ] + \nabla \bigg ( \frac{1}{B_o} \ \mathbf{u}_o + \frac{R_v}{B_g} \ \mathbf{u}_g \bigg ) = q_O(\mathbf{r})
(67) \partial_t \bigg [ \phi \ \bigg ( \frac{s_g}{B_g} + \frac{R_s \ s_o} {B_o} \bigg ) \bigg ] + \nabla \bigg ( \frac{1}{B_g} \ \mathbf{u}_g + \frac{R_s}{B_o} \ \mathbf{u}_o \bigg ) = q_G (\mathbf{r})
(68) \mathbf{u}_w = - k_a \ \frac{k_{rw}(s_w, s_g)}{\mu_w} \ ( \nabla P_w - \rho_w \ \mathbf{g} )
(69) \mathbf{u}_o = - k_a \ \frac{k_{ro}(s_w, s_g)}{\mu_o} \ ( \nabla P_o - \rho_o \ \mathbf{g} )
(70) \mathbf{u}_g = - k_a \ \frac{k_{rg}(s_w, s_g)}{\mu_g} \ ( \nabla P_g - \rho_g \ \mathbf{g} )
(71) P_o - P_w = P_{cow}(s_w)
(72) P_o - P_g = P_{cog}(s_g)
(73) s_w + s_o + s_g = 1



(74) (\rho \,c_{pt})_p \frac{\partial T}{\partial t}   - \ \phi \sum_{a = \{w,o,g \}} \rho_\alpha \ c_{p \alpha} \ \eta_{s \alpha} \ \frac{\partial P_\alpha}{\partial t}   + \bigg( \sum_{a = \{w,o,g \}} \rho_\alpha \ c_{p \alpha} \ \epsilon_\alpha \ \mathbf{u}_\alpha \bigg) \nabla P   + \bigg( \sum_{a = \{w,o,g \}} \rho_\alpha \ c_{p \alpha} \ \mathbf{u}_\alpha \bigg) \ \nabla T   - \nabla (\lambda_t \nabla T) = \rho_{\rm inj} \, c_{\rm inj} \, T_{\rm inj} \, q_{\rm inj}({\bf r})\, \delta({\bf r})

The disambiguation of the properties in the above equation is brought in The list of dynamic flow properties and model parameters.

The right sides of equations  (65) –  (67) suggest no sources of flow except the contacts between wells and reservoir which is specified by well models as boundary conditions (see below).


Initial Conditions



Initial temperature distribution is set as input:

T(0, \mathbf{r}) = T_0(\mathbf{r})


In case the simulation is performed over the undisturbed reservoir then initial temperature distribution is geothermal.


The initial condition on phase pressure, phase velocities and phase saturations is set by one of the following options: Equilibrium Start and Non-equilibrium Start.



Condition I – Equilibrium Start


Equilibrium Start means that flow was not happening before the start:  \{ \mathbf{u}_w = 0, \ \mathbf{u}_o = 0, \ \mathbf{u}_g =0 \} and correspondingly phase pressure \{ P_w, \ P_o, \ P_g \} and phase saturations  \{ s_w, \ s_o, \ s_g, \} were in stationary (not varying in time) conditions:

(75) \nabla \cdot \bigg ( \frac{1}{B_w} \ \mathbf{u}_w \bigg )_{t=0} = 0
(76) \nabla \cdot \bigg ( \frac{1}{B_o} \ \mathbf{u}_o + \frac{R_v}{B_g} \ \mathbf{u}_g \bigg )_{t=0} = 0
(77) \nabla \cdot \bigg ( \frac{1}{B_g} \ \mathbf{u}_g + \frac{R_s}{B_o} \ \mathbf{u}_o \bigg )_{t=0} = 0
(78) \mathbf{u}_w(0, \mathbf{r}) = - k_a \ \frac{k_{rw}(s_w, s_g)}{\mu_w} \ (\nabla P_w(0, \mathbf{r}) - \rho_w \ \mathbf{g} ) = 0
(79) \mathbf{u}_o(0, \mathbf{r}) = - k_a \ \frac{k_{ro}(s_w, s_g)}{\mu_o} \ ( \nabla P_o(0, \mathbf{r}) - \rho_o \ \mathbf{g} ) = 0
(80) \mathbf{u}_g(0, \mathbf{r}) = - k_a \ \frac{k_{rg}(s_w, s_g)}{\mu_g} \ ( \nabla P_g(0, \mathbf{r}) - \rho_g \ \mathbf{g} ) = 0
(81) P_o(0, \mathbf{r}) - P_w(0, \mathbf{r}) = P_{cow}(s_w)
(82) P_o(0, \mathbf{r}) - P_g(0, \mathbf{r}) = P_{cog}(s_g)
(83) s_w + s_o + s_g = 1


Condition II – Non-equilibrium Start


Non-equilibrium Start means that flow happening before the start:  \mathbf{u}_w^2 + \mathbf{u}_o^2 + \mathbf{u}_g^2 > 0  and correspondingly phase pressure  \{ P_w, \ P_o, \ P_g \} and phase saturations  \{ s_w, \ s_o, \ s_g, \} were in not in equilibrium:

(84) s_w(0, \mathbf{r}) + s_o(0, \mathbf{r}) + s_g(0, \mathbf{r}) = 1

pressure distribution  \{ P_w, \ P_o, \ P_g \} could be arbitrary providing the capillary constraints:

(85) P_o(0, \mathbf{r}) - P_w(0, \mathbf{r}) = P_{cow}(s_w)
(86) P_o(0, \mathbf{r}) - P_g(0, \mathbf{r}) = P_{cog}(s_g).


The phase velocities are initialized as:

(87) \mathbf{u}_w(0, \mathbf{r}) = - k_a \ \frac{k_{rw}(s_w, s_g)}{\mu_w} \ ( \nabla P_w(0, \mathbf{r}) - \rho_w \ \mathbf{g} )
(88) \mathbf{u}_o(0, \mathbf{r}) = - k_a \ \frac{k_{ro}(s_w, s_g)}{\mu_o} \ ( \nabla P_o(0, \mathbf{r}) - \rho_o \ \mathbf{g} )
(89) \mathbf{u}_g(0, \mathbf{r}) = - k_a \ \frac{k_{rg}(s_w, s_g)}{\mu_g} \ ( \nabla P_g(0, \mathbf{r}) - \rho_g \ \mathbf{g} )


In practice, the non-equilibrium conditions before the start  is usually a result of previous flow simulations for the same reservoir, sometimes using a different grid-structure.


External Boundary Condition 



The external boundary condition for the temperature is usually set by one if the two options:

External Temperature Boundary Condition I – Fixed Temperature

T(t, \mathbf{r}) |_{\Gamma_e} = T_e( \mathbf{r})

External Temperature Boundary Condition II – Fixed Heat Exchange

(90) \big( \mathbf{n}, \nabla T(t, \mathbf{r} \big) \big |_{\Gamma_e} = \zeta \cdot \big( T(t, \mathbf{r}) - T_e( \mathbf{r}) \big)

where  \zeta  – heat exchange coefficient at model boundary.


The external boundary condition for phase pressure, phase velocities and phase saturations is set by one of the two popular options:

External Pressure Boundary Condition I – Non-permeable boundary  \Gamma_e

(91) \big( \mathbf{n}, \ (\nabla P_\alpha(t, \mathbf{r}) - \rho_\alpha \mathbf{r}) \big) \big|_{\Gamma_e} = 0

where   \mathbf{n} – normal vector to the boundary  \Gamma_e and  \alpha = \{ w, o, g \}.

External Pressure Boundary Condition II – constant-pressure boundary  \Gamma_e

(92) P_\alpha(t, \mathbf{r}) \big|_{\Gamma_e} = P_i = const

where   \alpha = \{ w, o, g \}.



Well Model



Well flow model (don't get confused with Wellbore Flow Model) simulates the flow at the contact between well and reservoir thus relating the sandface flow rates and pressure distribution in reservoir around the well:

(93) P_w(t, \mathbf{r}) \big|_{\Gamma_{WRC}} = P_o(t, \mathbf{r}) \big|_{\Gamma_{WRC}} = P_g(t, \mathbf{r}) \big|_{\Gamma_{WRC}}= P_{wf}(t) \big|_{\Gamma_{WRC}}

where  \Gamma_{WRC} is a well-reservoir.

Bottom-hole pressure  P_{wf}(t) \big|_{\Gamma_{WFC}} = P_{wf}(t,h)  at the contact (at depth  h along-hole) is set by one of the three popular conditions (traditionally called "Controls"):

  • Well Condition I – Pressure Control

  • Well Condition II – Liquid Control

  • Well Condition III – Oil Control


The list of dynamic flow properties and model parameters



(t,x,y,z)

time and space corrdinates ,

z -axis is orientated towards the Earth centre,

(x,y) define transversal plane to the z -axis

\mathbf{r} = (x, \ y, \ z)

position vector at which the flow equations are set

q_{mW} = \frac{d m_W}{dt}

speed of water-component mass change in wellbore draining points

q_{mO} = \frac{d m_O}{dt}

speed of oil-component mass change in wellbore draining points

q_{mG} = \frac{d m_G}{dt}

speed of gas-component mass change in wellbore draining points

q_W = \frac{1}{\rho_W^{\LARGE \circ}} \frac{d m_W}{dt} = \frac{d V_{Ww}^{\LARGE \circ}}{dt} = \frac{1}{B_w} q_w

volumetric water-component flow rate in wellbore draining points recalculated to standard surface conditions

q_O = \frac{1}{\rho_O^{\LARGE \circ}} \frac{d m_O}{dt} = \frac{d V_{Oo}^{\LARGE \circ}}{dt} + \frac{d V_{Og}^{\LARGE \circ}}{dt} = \frac{1}{B_o} q_o + \frac{R_v}{B_g} q_g

volumetric oil-component flow rate in wellbore draining points recalculated to standard surface conditions

q_G = \frac{1}{\rho_G^{\LARGE \circ}} \frac{d m_G}{dt} = \frac{d V_{Gg}^{\LARGE \circ}}{dt} + \frac{d V_{Go}^{\LARGE \circ}}{dt} = \frac{1}{B_g} q_g + \frac{R_s}{B_o} q_o

volumetric gas-component flow rate in wellbore draining points recalculated to standard surface conditions

q_w = \frac{d V_w}{dt}

volumetric water-phase flow rate in wellbore draining points

q_o = \frac{d V_o}{dt}

volumetric oil-phase flow rate in wellbore draining points

q_g = \frac{d V_g}{dt}

volumetric gas-phase flow rate in wellbore draining points

q^S_W =\frac{dV_{Ww}^S}{dt}

total well volumetric water-component flow rate

q^S_O = \frac{d (V_{Oo}^S + V_{Og}^S )}{dt}

total well volumetric oil-component flow rate

q^S_G = \frac{d (V_{Gg}^S + V_{Go}^S )}{dt}

total well volumetric gas-component flow rate

q^S_L = q^S_W + q^S_O

total well volumetric liquid-component flow rate

P_w = P_w (t, \vec r)

water-phase pressure pressure distribution and dynamics

P_o = P_o (t, \vec r)

oil-phase pressure pressure distribution and dynamics

P_g = P_g (t, \vec r)

gas-phase pressure pressure distribution and dynamics

\vec u_w = \vec u_w (t, \vec r)

water-phase flow speed distribution and dynamics

\vec u_o = \vec u_o (t, \vec r)

oil-phase flow speed distribution and dynamics

\vec u_g = \vec u_g (t, \vec r)

gas-phase flow speed distribution and dynamics

P_{cow} = P_{cow} (s_w)

capillary pressure at the oil-water phase contact as function of water saturation


P_{cog} = P_{cog} (s_ g)

capillary pressure at the oil-gas phase contact as function of gas saturation

k_{rw} = k_{rw}(s_w, \ s_g)

relative formation permeability to water flow as function of water and gas saturation

k_{ro} = k_{ro}(s_w, \ s_g)

relative formation permeability to oil flow as function of water and gas saturation

k_{rg} = k_{rg}(s_w, \ s_g)

relative formation permeability to gas flow as function of water and gas saturation

\phi = \phi(P)

porosity as function of formation pressure

k_a = k_a(P)

absolute formation permeability to air

\vec g = (0, \ 0, \ g)

gravitational acceleration vector

g = 9.81 \ \rm m/s^2

gravitational acceleration constant

\rho_\alpha(P,T)

mass density of \alpha-phase fluid

\mu_\alpha(P,T)

viscosity of \alpha-phase fluid

\lambda_t(P,T,s_w, s_o, s_g)

effective thermal conductivity of the rocks with account for multiphase fluid saturation

\lambda_r(P,T)

rock matrix thermal conductivity

\lambda_\alpha(P,T)

thermal conductivity of \alpha-phase fluid

\rho_r(P,T)

rock matrix mass density

\eta_{s \alpha}(P,T)

differential adiabatic coefficient of \alpha-phase fluid

c_{pr}(P,T)

specific isobaric heat capacity of the rock matrix

c_{p\alpha}(P,T)

specific isobaric heat capacity of \alpha-phase fluid

\epsilon_\alpha (P, T)

differential Joule–Thomson coefficient of \alpha-phase fluid


Computational Model



Modified Black Oil Reservoir Flow Grid Computation @model


See Also


Petroleum Industry / Upstream / Subsurface E&P Disciplines / Dynamic Flow Model Reservoir Flow Model (RFM)
Petroleum Industry / Upstream / Subsurface E&P Disciplines / Fluid (PVT) Analysis / Fluid @model / Modified Black Oil fluid @model
Petroleum Industry / Upstream / Production / Subsurface Production / Well & Reservoir Management / Formation pressure / Multiphase formation pressure

Modified Black Oil Reservoir Flow Grid Computation @model

Derivation of Derivation of Modified Black Oil Reservoir Flow @mode




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