Process Intensification and Integration for Sustainable Design. Группа авторов
Чтение книги онлайн.
Читать онлайн книгу Process Intensification and Integration for Sustainable Design - Группа авторов страница 21
![Process Intensification and Integration for Sustainable Design - Группа авторов Process Intensification and Integration for Sustainable Design - Группа авторов](/cover_pre844053.jpg)
Figure 2.11 Revenue for the high acid gas case and base case (MM$/yr).
As shown in Table 2.8, the additional TCI required to treat this stream is not significant, as compared with the additional revenue, and therefore this stream is clearly worth treating (IROI > 10%).
Table 2.8 Incremental return on investment for high acid case.
HA feed | |
ΔAnnual net profit (MM$/yr) | 11.8 |
ΔTotal capital investment (MM$/yr) | 6.15 |
Incremental ROI (%) | 192 |
2.5.4 Safety Index Results
PRI is a relative comparison. The exact values from the calculations are not meaningful, only the relative comparison between different process routes, or in this case different incoming feeds. Only streams where a significant change in composition, pressure, or fluid density occurs were included in the calculation.
One significant weakness of PRI is that is uses the overall average value of each property for all the streams, effectively treating every stream considered as if it has the same flow rate (and thus same potential risk). This leads to misleading results; to give a more truthful picture, the values of each of the four properties used to calculate PRI (mass heating value, fluid density, pressure, and explosiveness) were multiplied by their flow rates as presented in Table 2.9.
Table 2.9 Results from modified process route index calculations.
Feed #1 | Feed #2 | Feed #3 | Feed #4 | Feed #5 | HA feed | |
Overall | 19.48 | 27.85 | 31.83 | 34.03 | 34.43 | 26.83 |
The lower methane cases are less safe to process. This is because the flows are generally larger in these designs because dehydration is more difficult, and because the fractionation process has higher flow rates due to higher NGL content. Nonetheless there is really not a significant difference in these process designs from a safety perspective. Therefore economic criteria should be the main concern for deciding whether or not to treat streams.
2.5.5 Sensitivity Analysis
One issue of great concern for shale gas producers is price volatility. The price of heating value and of NGLs has fluctuated significantly over the last 15 years [33]. The average and standard deviation for NGL and heating value price data were determined assuming a normal distribution (see Table 2.10) [25].
Table 2.10 Maximum, minimum, average, and standard deviation for price data.
Maximum | Minimum | Average | Standard deviation | |
Heating value ($/MMBtu) | US$13.42 | US$1.72 | US$4.40 | US$2.22 |
Ethane ($/gal) | US$1.39 | US$0.14 | US$0.43 | US$0.27 |
Propane ($/gal) | US$1.89 | US$0.36 | US$0.97 | US$0.37 |
n‐Butane ($/gal) | US$2.31 | US$0.49 | US$1.26 | US$0.47 |
A Monte Carlo simulation with 10 000 iterations was performed to find the probability of not being profitable for the base case (when ROI < 10%). Variables were set to be distributed normally in the simulation program. The probability of losing money was about 36%. The average ROI was about 59%; however the standard deviation from the Monte Carlo was approximately 135%. Clearly the shale gas processing business is potentially very profitable, but also very risky. The measured contributions to variance on ROI are shown in Figure 2.12.
Figure 2.12 Measured contributions to variance on ROI for the inputs.
By far the biggest contributor is the heating value, which affects both raw material cost and the sales gas price. This makes sense because methane is the predominant component for this feed (77.78 mol%).
2.5.5.1 Heating Value Cases
Next a few specific cases are considered as shown in Table 2.11. The heating value price affects both the methane and the feedstock price. A higher price for heating value increases both the methane sales prices (which increases potential profitability) and increases the feedstock price (which decreases potential profitability). A sensitivity analysis is used to show which of these counteracting effects is more significant.
Table 2.11 Description of Cases 1–3 for sensitivity analysis.
Case 1 | Case 2 | Case 3 | |
Heating value | −1 Standard deviation | Average | +1 Standard deviation |
NGL prices | Average | Average | Average |
The results in Figure 2.13 show the process is more profitable at lower heating value prices. This means