1. Motivation

One of the most important objectives of the well testing is to assess the drainable oil reserves and reservoir properties around tested well.

This particularly becomes important in appraisal drilling as well testing is the only source of this information.

BUS – Build-up Survey

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

The primary hard data deliverables are:

formation pressure $\begin{array}{l}P_i\end{array}$
skin-factor S
average transmissibility in drainage area $\begin{array}{l}\sigma\end{array}$
time to reach the reservoir boundary $\begin{array}{l}t_e\end{array}$

The conditional deliverables from build-up survey would be:

Deliverables

Description

Non-BUS Input Parameters

Key Uncertainties

(1)	$\begin{array}{l}\displaystyle V_o = \frac{4 \, \sigma \, t_e \, (1-s_{wi})}{c_t}\end{array}$

where $\begin{array}{l}c_t\end{array}$ is total compressibility:

(2)	$\begin{array}{l}\displaystyle c_t = c_r + (1-s_{wi}) \, c_o + s_{wi} \, c_w\end{array}$

and $\begin{array}{l}\{ c_r, \, c_o \, c_w \}\end{array}$ are rock, oil and water compressibility.

Drainable oil reserves

The rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$ is defined from core lab study or empirical porosity correlations

Fluid compressibility $\begin{array}{l}\{ c_o , \, c_w \}\end{array}$ from PVT

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$ from SCAL

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

(3)	$\begin{array}{l}\displaystyle A_e = 4 \, \chi \, t_e\end{array}$

where $\begin{array}{l}\chi\end{array}$ is pressure diffusivity:

(4)	$\begin{array}{l}\displaystyle \chi = \big< \frac{k}{\mu} \big> \, \frac{1}{\phi \, c_t}\end{array}$

where $\begin{array}{l}\phi\end{array}$ is reservoir porosity, $\begin{array}{l}\big< \frac{k}{\mu} \big>\end{array}$ is fluid mobility:

(5)	$\begin{array}{l}\displaystyle \big< \frac{k}{\mu} \big> = k_a \, \bigg[ \frac{k_{rw}}{\mu_w} + \frac{k_{ro}}{\mu_o} \bigg]\end{array}$

$\begin{array}{l}k_a\end{array}$ is absolute permeability to air,

$\begin{array}{l}k_{rw}, \, k_{ro}\end{array}$ are relative permeabilities to water and oil,

$\begin{array}{l}\mu_w, \mu_o\end{array}$ are water and oil viscosities

Drainage area

Formation porosity $\begin{array}{l}\phi\end{array}$

Absolute permeability to air $\begin{array}{l}k_a\end{array}$ from core study

Relative permeabilities $\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$ from SCAL

Fluid viscosities $\begin{array}{l}\{ \mu_w, \mu_o \}\end{array}$ from PVT

Absolute permeability to air $\begin{array}{l}k_a\end{array}$

Relative permeabilities

$\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$

(6)	$\begin{array}{l}\displaystyle h = \sigma \, \bigg< \frac{k}{\mu} \bigg>^{-1}\end{array}$

Effective reservoir thickness

Absolute permeability to air $\begin{array}{l}k_a\end{array}$ from core study

Relative permeabilities $\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$ from SCAL

Fluid viscosities $\begin{array}{l}\{ \mu_w, \mu_o \}\end{array}$ from PVT

Absolute permeability to air $\begin{array}{l}k_a\end{array}$

Relative permeabilities $\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$

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.

SPT – Self-Pulse Testing

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

The primary hard data deliverables are:

formation pressure $\begin{array}{l}P_i\end{array}$
skin-factor S
near $\begin{array}{l}\sigma_{near}\end{array}$ and far $\begin{array}{l}\sigma_{far}\end{array}$ zone transmissibility
near $\begin{array}{l}\chi_{near}\end{array}$ and far $\begin{array}{l}\chi_{far}\end{array}$ zone pressure diffusivity
time to reach the reservoir boundary $\begin{array}{l}t_e\end{array}$

The BUS correlates pressure decline to change in production rate (usually from constant production rate to shut-in) and it strongly depends on formation transmissibility $\begin{array}{l}\sigma\end{array}$ .

The SPT is correlating pressure variation with flowrate variation and tracks pressure response amplitude which depends on formation transmissibility $\begin{array}{l}\sigma\end{array}$ and the time lag between flowrate variation and pressure response which depends on formation diffusivity $\begin{array}{l}\chi\end{array}$ .

This allows estimating effective formation thickness $\begin{array}{l}h\end{array}$ directly from field survey without assumptions on core-based permeability (compare with (6)) and consequently leads to assessing the drainange area $\begin{array}{l}A_e\end{array}$ , fluid mobility $\begin{array}{l}\bigg< \frac{k}{\mu} \bigg>\end{array}$ and absolute permeability $\begin{array}{l}k_a\end{array}$ with lesser uncertainties than in BUS:

Deliverables

Description

Non-BUS Input Parameters

Key Uncertainties

(7)	$\begin{array}{l}\displaystyle h = \frac{\sigma}{\phi \, c_t \, \chi}\end{array}$

Effective reservoir thickness

Formation porosity $\begin{array}{l}\phi\end{array}$

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

Fluid compressibility $\begin{array}{l}\{ c_o , \, c_w \}\end{array}$

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

(8)	$\begin{array}{l}\displaystyle A_e = \frac{4 \, \sigma \, t_e}{c_t \, h}\end{array}$

Drainage area

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

Fluid compressibility $\begin{array}{l}\{ c_o , \, c_w \}\end{array}$

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

(9)	$\begin{array}{l}\displaystyle \bigg< \frac{k}{\mu} \bigg> = \chi \, \phi \, c_t\end{array}$

Fluid mobility

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

Fluid compressibility $\begin{array}{l}\{ c_o , \, c_w \}\end{array}$

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

(10)	$\begin{array}{l}\displaystyle k_a = \frac{\bigg< \frac{k}{\mu} \bigg>}{\bigg[ \frac{k_{rw}}{\mu_w} + \frac{k_{ro}}{\mu_o} \bigg]}\end{array}$

Absolute permeability

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

Relative permeabilities $\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$

Fluid viscosities $\begin{array}{l}\{ \mu_w, \mu_o \}\end{array}$

Fluid compressibility $\begin{array}{l}\{ c_o , \, c_w \}\end{array}$

Rock compressibility $\begin{array}{l}c_r(\phi)\end{array}$

Initial water saturation $\begin{array}{l}s_{wi}\end{array}$

Relative permeabilities $\begin{array}{l}\{ k_{rw}, \, k_{ro} \}\end{array}$

The latter is usually stacked up against core-based permeability to validate the core samples and assess the effects of macroscopic features which are overlooked at core-plug size level.

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

Expand more on SPT

Conventional pressure transient analysis relates pressure build-up to the rate step change and assesses transmissibility, which is a product of permeability and thickness.

Estimation of permeability and thickness separately requires transmissibility and pressure diffusivity and normally available in interference test where pressure response delay is measured in hours or longer and can be effectively captured.

The effects of the pressure delay in single well test are so small (seconds/minutes) that conventional build-up can not capture it reliably and hence pressure diffusivity can not be assessed.

In SPT the rate undergoes sequential step changes which allows dasta accumulation and more accurate measurement of pressure build-up delay and through this assess pressure diffusivity.

This effect is accurately described by analytical solution of diffusivity equation and meets practical observations.

In order to numerically reproduce a short-term pressure-rate lag in single-well survey one needs a dedicated numerical solver since the required mesh size is comparable to the well size and conventional Peaceman well model does not work.

The usual SPT workflow includes several cycling tests with different frequencies, the lower the frequency the longe 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 the well location.

2. Objectives

Assess reservoir volume around well
Assess reservoir permeability and thickness variation around well

3. Deliverables


V_hc	Potential hydrocarbon reserves
V_e	Drainage volume
A_e	Drainage area
k_near	Permeability of the near-reservoir zone
h_near	Effective thickness of the near-reservoir zone
k_far	Permeability of the far-reservoir zone
h_far	Effective thickness of the far-reservoir zone
S	Skin-factor
P_u(t)	Deconvolution of the long-term unit-rate response

4. Inputs

Property	Description	Data Source
B_o	Oil Formation Volume Factor	PVT samples
c_o	Oil compressibility	PVT samples
c_w	Water compressibility	PVT samples
c_r	Rock compressibility	PVT samples
s_wi	Initial water saturation	Core samples
$\begin{array}{l}\phi\end{array}$	Porosity	Core samples

5. Procedure

Test = Test 1 + Test 2 + Test 3

Test 1 = high freq pulsations (10 pulses with period T)
Test 2 = mid freq pulsations (10 pulses with with period 5T)
Test 3 = Low freq pulsations (10 pulses with period 25 T)

So that total duration of the test is 310 T.

Typically T = 3 hrs and total test duration is around 40 days.

6. Interpretation

Numerical model
1. Single well with circle boundary
2. High density LGR
3. High density time grid (seconds)
Automated pressure match in PolyGon software

Page tree

1. Motivation

BUS – Build-up Survey

SPT – Self-Pulse Testing

2. Objectives

3. Deliverables

4. Inputs

5. Procedure

6. Interpretation

References

Page tree

SPT – Self Pulse Test

1. Motivation

BUS – Build-up Survey

SPT – Self-Pulse Testing

2. Objectives

3. Deliverables

4. Inputs

5. Procedure

6. Interpretation

References