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q(t)=q_0 \cdot \exp \left[ -D_0 \cdot \left( t+ \frac{a \cdot t^{n+1}}{n+1} \right)  int_0^t D(Q(t)) \, dt  \right] 



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D(tQ) = D_0 \cdot ( 1 + a\cdot t^n {\rm ANN}(Q)


where

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bodyq_0 = q(t=0)

Initial production rate of a well (or groups of wells)

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body

D_0 > 0

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bodya

model parameter characterizing production decline

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bodyn

model parameter characterizing production decline

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body--uriencoded--\displaystyle D(t) =- \frac%7Bdq%7D%7BdQ%7D

Production decline rate

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body--uriencoded--\displaystyle Q(t)=\int_0%5et q(t) dt

cumulative production

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body--uriencoded--%7B\rm ANN%7D(Q)

artificial neural-network regression of  Production decline rate 

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bodyD
 on cumulative production 
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bodyQ


DCA ANNDCA Power Law decline is an empirical correlation for production from both finite-reserves 

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body--uriencoded--Q_%7B\rm max%7D \leq \infty
or infinite-reserves 
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body--uriencoded--Q_%7B\rm max%7D = \infty
 reservoir. 

Alternative form

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reservoirs. 


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q(t)=q_0 \cdot \exp \left( -D_{\infty}t- \left( t/\tau \right)^{n} \right)

where

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bodyD_{\infty}

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decline decrement at long times (the higher the

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bodyD
the stronger is decline)

See Also

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Petroleum Industry / Upstream /  Production / Subsurface Production / Field Study & Modelling / Production Analysis / Decline Curve Analysis

DCA Arps @model ] [ Production decline rate ]

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