Process Intensification and Integration for Sustainable Design. Группа авторов
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Figure 2.13 Results for Cases 1–3 for the sensitivity analysis.
2.5.5.2 NGL Price Cases
Figure 2.14 shows NGL prices over time are correlated. Therefore cases where the NGL product prices fluctuated together were considered (Table 2.12). Since for a normal distribution 99.7% of the values lie within 3 standard deviations of the mean, ±3 standard deviations were chosen for the cases (prices were not allowed to be negative). Since the main question is whether the process will be profitable or not, only the deviations in the direction that would make the process less profitable were examined.
Figure 2.14 Price of products over time [34].
Table 2.12 Description of cases for sensitivity analysis.
Case 4 | Case 5 | Case 6 | |
Heating value | Average | Average | Average |
NGL prices | −1 Standard deviation | −2 Standard deviation | −3 Standard deviation |
As can be seen in Figure 2.15, for even a drop of 1 standard deviation in NGL prices, the ROI value will become negative. This occurs because the standard deviations of the product prices are very high. An additional calculation shows that to achieve an ROI of more than 10%, product prices cannot drop more than 16.5%, assuming an average heating value price.
Figure 2.15 Results for Cases 4–6 for the sensitivity analysis.
2.6 Conclusions
A methodology was developed for process design under uncertainty for a shale gas treatment plant. An integrated approach of process simulation, design under uncertainty, techno‐economic analysis, and safety assessment was used to determine the optimal design of the gas treatment plant. A number of feeds with varying inlet compositions were examined to represent the uncertain compositions of shale gas. A case study was carried out for data from the Barnett Shale Play.
A key observation is the increase of both revenue and processing costs with increasing NGL content. As measured by ROI, all feeds (including the high acid case) are worth treating, except the high methane case (Feed #1). From the sensitivity analysis, it can be concluded that for the base case, shale gas processing is still profitable for even the highest feedstock prices. However, a drop of one standard deviation in product prices will make processing highly unprofitable.
Appendices
Included in the Appendix are key parameters for the process simulations. Further guidance can be found in the Bryan Research & Engineering guide [24].
Appendix A: Key Parameters for the Dehydration Process
2.A
Table 2.A.1 Dehydration column parameters for the base case (Feed #3).
Column | Feed flow rate (MMSCFD) | T (°F) | P (psig) | Number of trays |
Contactor | 150 | 101 | 996–998 | 2 |
Regenerator | 0.830 | 214–308 | 0–4 | 4 |
Feed flow rate is a standard vapor volumetric flow rate.
Table 2.A.2 Makeup composition for the base case (Feed #3).
Stream | Water (mass%) | TEG (mass%) |
Makeup | 0.1 | 99.9 |
Table 2.A.3 Glycol circulation rate for the base case (Feed #3).
Stream | Circulation rate (gal/lb) |
21 | 2–5 gal glycol/lb water in stream 1 |
Appendix B: Key Parameters for the Turboexpander Process
2.B
Table 2.B.1 Demethanizer column parameters.
Column | Total feed flow rate (MMSCFD) | T (°F) | P (psig) | Number of trays | Light/heavy key |
Demethanizer | 202 | −111 to 65.4 | 250–254 | 10 | Methane/ethane |
Feed flow rate is a standard vapor volumetric flow rate.
Table 2.B.2 Low temperature separator (LTS) inlet temperature.
Stream | T (°F) |
10 | −25 |
Table 2.B.3 Outlet pressure for the pressure changing equipment.
Stream | P (psig) |
13 | 250 |