1. Motivation
One of the most important objectives of the well testing is to assess the drainable oil reserves around tested well.
This particularly becomes important in appraisal drilling.
In conventional pressure build-up survey in a single-well reservoir the primary hard data deliverables are:
- formation pressure
P_i
- skin-factor S
- average transmissibility in drainage area
\sigma
- time to reach the reservoir boundary t_e
The conditional deliverables from build-up survey would be:
Deliverables | Description | Assumptions | ||||||
---|---|---|---|---|---|---|---|---|
where c_t is total compressibility:
and \{ c_r, \, c_o \, c_w \} are rock, oil and water compressibility. | Drainable oil reserves | The rock compressibility c_r(\phi) is defined from core lab study or empirical porosity correlations Fluid compressibility \{ c_o \, c_w \} is estimated from PVT study Initial water saturation s_{wi} is estimated from SCAL | ||||||
where \chi is pressure diffusivity:
where \phi is reservoir porosity, \big< \frac{k}{\mu} \big> is fluid mobility:
k_a is absolute permeability to air,
\mu_w, \mu_o are water and oil viscosities | Drainage area | |||||||
Conventional pressure build-up survey in a single-well reservoir is normally providing assessment of:
- average transmissibility in drainage area
\sigma
- drainage area around the well
A_e
- formation pressure
P_i
- skin-factor S
where
| transmissibility | ||
| mobility | ||
It is important to notice that drainage area A_e is calculated based on the permeability estimations from core study and compressibility estimation from porosity correlations which may not be representative of the whole drainage area:
(8) | A_e = 4 \, \chi \, t_e |
where t_e time to reach the reservoir boundary from BUS log-log plot and \chi is pressure diffusivity which is used to translate t_e into a drainage area
(9) | \chi = \big< \frac{k}{\mu} \big> \, \frac{1}{\phi \, c_t} |
In regular workflow one pulls permeability
k from core studies, then estimates diffusivity
\chi from
(4) and then calculates average reservoir thickness in drainage area as
(10) | h = \phi \, c_t \, \frac{\sigma}{\chi} |
which leads to assessment of drainable oil volume as
(11) | V_o = (1-s_{wi}) \, \phi \, h \, A_e |
This methodology is strongly dependent on core-based permeability which may not be representative of the whole drainage area.
The alternative way of
2. Objectives
- Assess reservoir volume around well
- Assess reservoir permeability and thickness variation around well
3. Deliverables
Vhc | Potential hydrocarbon reserves |
Ve | Drainage volume |
Ae | Drainage area |
ks | Permeability of the skin-zone |
hs | Effective thickness of the skin-zone |
knear | Permeability of the near-reservoir zone |
hnear | Effective thickness of the near-reservoir zone |
kfar | Permeability of the far-reservoir zone |
hfar | Effective thickness of the far-reservoir zone |
S | Skin-factor |
Pu(t) | Deconvolution of the long-term unit-rate response |
4. Inputs
Property | Description | Data Source |
---|---|---|
Bo | Oil Formation Volume Factor | PVT samples |
co | Oil compressibility | PVT samples |
cw | Water compressibility | PVT samples |
cr | Rock compressibility | PVT samples |
swi | Initial water saturation | Core samples |
\phi | Porosity | Core samples |
5. Procedure
- Test = Test 1 + Test 2 + Test 3
- Test 1 = high freq pulsations (10 pulses with 0.3 day)
- Test 2 = mid freq pulsations (10 pulses with 1.5 day)
- Test 3 = Low freq pulsations (5 pulses with 5.5 day)
6. Interpretation
- Numerical model
- Single well with circle boundary
- High density LGR
- High density time grid (seconds)
- Single well with circle boundary
- Automated pressure match in PolyGon software
References
\sigma