General Reservoir & Production Engineering Workflows

1

Data Review

Look for consistency between rates and pressures. Identify abhorrent data

Common Issues with Production Data Include:

Refer to Rate-Pressure Correlation

2

Data Clean

Remove spurious data from analysis (in AFA, this is done effectively through advanced data science)

a. This may include averaging, smoothing algorithms, splines, wavelets, etc

b. Outlier detection

3

1. Identify Flow Regimes

a. Time-Rate-Pressure Correlation using Diagnostic Plots:

1. vs time or material balance time (t_mb); See Pressure Normalized Decline Analysis

2. or vs Sqrt[time] (I.e. Linear Analysis)

3. Production Exploration, q or cumulative production

4. Decline Analysis used to supplement the more rigorous model-based methods. Note there must be sufficient data for extrapolation.

   1. The strength of such methods are the simplicity that these models have to data fitting.

   2. The weakness is that they are not true solutions to fluid flow in porous media.

b. Analytical Model Using FMB and Rate Transient Analysis (RTA) or related Plots:

1. Normalized Pressure Integral (NPI) Plots,

2. Beta Plots,

3. Blasingame Plots,

4. Flowing Material Balance and FMB Productivity Index (PI) plots

   1. Very useful for establishing the presence of boundary-dominated flow and to estimate OHIP. Often useful even in the presence of significant or extreme data bias.

5. and other plots (in AFA, this is an automated procedure).

4

History Match

Compare Physics (or Science) Model to the observed raw data

5

Refine Model Parameters

A 2nd or 3rd pass of review may be required,.