Page History

BUS – Build-up Survey

SPT – Self-Pulse Testing

Conventional single-well testing is based on long-term monitoring of downhole pressure response to the step change in flow rate (usually shut-in or close-in).

The primary hard data deliverables are:
 

• formation pressure 

  LaTeX Math Inline
  body P_i

  
  
  
• skin-factor S
   
• average transmissibility in drainage area 

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  body \sigma

  
  
  
• time to reach the reservoir boundary 

  LaTeX Math Inline
  body t_e

The conditional deliverables from build-up survey would be:

V_o =  \frac{4 \, \sigma \, t_e \, (1-s_{wi})}{c_t}

c_t = c_r + (1-s_{wi}) \, c_o + s_{wi} \, c_w

A_e = 4 \, \chi \, t_e

\chi = \Big< \frac{k}{\mu} \Big> \, \frac{1}{\phi \, c_t}

\Big< \frac{k}{\mu} \Big> = k_a \, \bigg[ \frac{k_{rw}}{\mu_w} + \frac{k_{ro}}{\mu_o} \bigg]

h = \sigma \, \bigg< \frac{k}{\mu} \bigg>^{-1}

As one can see, the drainage area and the reservoir thickness are conditioned by core data which may not be representative of the whole drainage area.

The single-well self-pulse test is based on long-term monitoring of downhole pressure response to the periodic rate step change (usually shut-in or close-in).

If flowrate 

The primary hard data deliverables are:

• formation pressure 

  LaTeX Math Inline
  body P_i

  
  
  
• skin-factor S
   
• near 

  LaTeX Math Inline
  body \sigma_{near}

   and far 

  LaTeX Math Inline
  body \sigma_{far}

   zone transmissibility 
  
  
• near 

  LaTeX Math Inline
  body \chi_{near}

   and far 

  LaTeX Math Inline
  body \chi_{far}

   zone pressure diffusivity 
  
  
• time to reach the reservoir boundary 

  LaTeX Math Inline
  body t_e

The SPT is correlating pressure variation with pre-designed flowrate variation sequence and tracks:

• pressure response amplitude which depends on formation transmissibility 

  LaTeX Math Inline
  body \sigma

   

and

• time lag between flowrate variation and pressure response which depends on formation diffusivity 

  LaTeX Math Inline
  body \chi

  .

This allows estimating effective formation thickness 

h = \frac{\sigma}{\phi \, c_t \, \chi}

A_e = \frac{4 \, \sigma \, t_e}{c_t \, h}

\Big< \frac{k}{\mu} \Big>  = \chi \, \phi \, c_t

k_a =   \frac{\Big< \frac{k}{\mu} \Big>}{\bigg[ \frac{k_{rw}}{\mu_w} + \frac{k_{ro}}{\mu_o} \bigg]}

The absoluite permeability from SPT 

Running SPT in two different cycling frequences allows assessing the near and far resevroir zones spearately.

The usual SPT workflow includes several cycling tests with different frequencies, the lower the frequency the longer the scanning range.

This captures variation of permeability and thickness when moving away from well location.

Together with deconvolution, the SPT is reproducing conventional PTA information and providing additional data on pressure diuffusivity.

This maybe used as estimation of permeability and thickness separately and their variation away from well location.