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Specific type of Production Analysis (PA) workflow based on correlation between injection rates history and production rate history with account of bottomhole pressure history.

In case the bottomhole pressure data is not available it is considered constant over time.

Motivation



Production rate in producing well depends on its productivity index J, current formation pressure p_e and current BHP p_{wf}:

(1) q_1^{\uparrow}(t)=J \cdot \left( p_e(t) - p_{wf}(t) \right)

and as such depends on completion/lift settings (defining p_{wf}(t)) and how formation pressure is maintained p_e = p_e(t) over time.

It keeps declining due to the offtakes:

(2) p_e(t) = p_e[q_1^{\uparrow}(t), q_2^{\uparrow}(t), q_3^{\uparrow}(t), \dots]

and maintained by either aquifer or Fluid Injection and in the latter case depends on injection rates:

(3) p_e(t) = p_e[q_1^{\downarrow}(t),q_2^{\downarrow}(t),q_3^{\downarrow}(t),\dots ]

The combination of (1)(2) and (3) lead to the correlation between production rates, injection rates and bottomhole pressure variation.


The ultimate purpose of CRM is to correlate the long-term (few months or longer) injection rates history with production rates history and BHP history (recorded by PDG).

It is essentially based on the fact that production rate responds to changes in BHP and offset injection.


The major assumptions in CRM model are:


Assumption 2 means that interference between producers is fairly constant in time despite the rate variations and their impact on the dynamic drainage volumes.


Goals

Objectives

Identify and prioritise production optimisation opportunitiesGenerate production and formation pressure forecasts based on the bottom-hole pressure and injection rates
Identify and prioritise redevelopment opportunitiesAssess productivity index of producing wells
Identify and prioritise surveillance candidatesAssess dynamic drainage volume around producing wells

Quantify connectivity between injectors and producers

Assess water flood efficiency against expectations and / or between wells or well groups

Advantages









Limitations

Fast-trackIt only models injector-producer system
Requires minimum input data (BHP history, fowrate history and FVF)Requires eventful history of injection rates variations

Robust procedure (no manual setups)

Requires productivity index of producers to stay constant
Does not involve full-field 3D dynamic modelling and associated assumptionsRequires the drainage volumes of all producers stay the same throughout the modelling period

Only applicable for specific subset of PSS fluid flow regimes


Technology



The CRM trains linear correlation between variation of production rates against variation of injection rates with account of bottom-hole pressure history records in producers.

See Capacitance-Resistivity Model @model


InputsOutputs
Production rate historyProductivity Index for the focus producer
Bottom-hole pressure historyDrainage volume by the focus produce producer
Injection rate historyShare of injection going towards the focus producer
PVT model




See Also


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

Capacitance-Resistivity Model @model ]


References



Nguyen, A. P., Kim, J. S., Lake, L. W., Edgar, T. F., & Haynes, B. (2011, January 1). Integrated Capacitance Resistive Model for Reservoir Characterization in Primary and Secondary Recovery. Society of Petroleum Engineers. doi:10.2118/147344-MS

Holanda, R. W. de, Gildin, E., & Jensen, J. L. (2015, November 18). Improved Waterflood Analysis Using the Capacitance-Resistance Model Within a Control Systems Framework. Society of Petroleum Engineers. doi:10.2118/177106-MS



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