Production Analysis Case Study
Read this journal article. The study uses production analysis to develop a robust workflow and help in designing sustainable shale production. Figure 2 depicts an initial production analysis. What would an organization need to collect production parameters?
Introduction
Probabilistic evaluation
In this stage, the uncertainty overlooked in stage 1 is considered and evaluated. Each fixed parameter in the previous stage is now given an initial distribution (Table 1). Correlation between porosity and saturation was assumed to be a positive correlation, and that between the fracture numbers and fracture half-length was assumed to be a negative correlation. Next, a simulation was performed to refine the assumed distribution and to forecast the possible production. The initial and final distribution of the parameters is summarized in Table 1. Figure 7 shows P10, P50, and P90 forecast for Well 1 and Well 2. Fracture networks and fracture number are two of the major parameters that affect gas production from shale gas reservoirs.
Table 1 Initial and final distribution of uncertain completion parameters
| Parameters | Initial distribution | Final distribution | ||||||
|---|---|---|---|---|---|---|---|---|
| Distribution type | Min | Max | Mean | Distribution type | Mean | P10 | P90 | |
| Number of fractures | Triangular | 32 | 63 | 48 | Normal | 47 | 57 | 38 |
| Fracture half-length (ft) | Uniform | 30 | 250 | – | Log-normal | 118 | 208 | 46 |
| Fracture conductivity (N/A) | Uniform | 5 | 300 | – | Normal | 21 | 32 | 16 |
| Inner permeability | Uniform | 90 | 400 | – | Log-normal | 162 | 290 | 117 |
| Outer permeability | Uniform | 20 | 90 | – | Log-normal | 25 | 34 | 20 |
Fig. 7
Forecasted Normalized Gas Rate Versus Normalized Time (Semi-Log Scale)