{"id":2327,"date":"2016-06-06T16:13:11","date_gmt":"2016-06-06T21:13:11","guid":{"rendered":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/?p=2327"},"modified":"2016-06-06T16:13:11","modified_gmt":"2016-06-06T21:13:11","slug":"projecting-the-performance-of-adsorption-dehydration-process","status":"publish","type":"post","link":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/2016\/06\/projecting-the-performance-of-adsorption-dehydration-process\/","title":{"rendered":"Projecting the Performance of Adsorption Dehydration Process"},"content":{"rendered":"<p>The <a href=\"http:\/\/www.jmcampbell.com\/tip-of-the-month\/2014\/12\/troubleshooting-gas-liquid-separators-removal-of-liquids-from-the-gas\/\">May 2015 tip of the month<\/a> (TOTM) [1] presented a method which allows the users to estimate the decline of their adsorbent based on only one performance test run (PTR) for molecular sieve dehydrators using low pressure regeneration. This permits early formulation of a credible action plan. Site-specific factors will determines an adsorption unit\u2019s decline curve.\u00a0Consequently, conducting more than PTR is highly recommended. A poorly performing inlet separator, for example, could result in a unit exhibiting a more pronounced decline than indicated by the generic performance decline curves.<\/p>\n<p>One can utilize the May 2015 TOTM methodology effectively by developing a spreadsheet or a computer program. Therefore, based on this methodology, we have developed a computer module to perform all of the calculations. This computer module has been coupled with the PetroSkills\u00a0| John M Campbell GCAP (Gas Conditioning and Processing Software) [2]. This tip presents this computer model\u2019s numerical and graphical results for the same case study of May 2015 TOTM.<\/p>\n<p>The cyclical heating\/cooling of the adsorbent results in a capacity (mass of water per 100 mass of adsorbent) decline due to a gradual loss of crystalline structure and\/or pore closure.\u00a0 A more troublesome cause of capacity decline is contamination of the molecular sieves due to liquid carryover from the upstream separation equipment.<\/p>\n<p>The molecular sieve capacity decline curve is an essential element of this methodology. Figure 18.8 in Gas Conditioning and Processing, Volume 2: The Equipment Modules (9<sup>th<\/sup> Edition) [3], presents a generic molecular sieve capacity decline curves. An expanded form of Figure 18.8 with five curves is shown in Figure 1. Shown in this figure are \u201cGood\u201d, \u201cGood-Average (G_A)\u201d, \u201cAverage\u201d, \u201cAverage-Poor (A_P)\u201d, and \u201cPoor\u201d curves that are a function of site specific factors. The life of the adsorbent is a function of the number of cycles, not the elapsed calendar time. Locating one data point on Figure 1 from a performance test run (PTR) allows us to generate the decline curve of the unit in question. For computer programming purpose, we have developed a simple mathematical model. For more detail regarding adsorption dehydration process see references [1 and 3].<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2328\" aria-describedby=\"caption-attachment-2328\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"wp-image-2328\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig1.jpg?resize=700%2C424\" alt=\"Figure 1. A generic molecular sieve capacity decline curves\" width=\"700\" height=\"424\" srcset=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig1.jpg?w=776 776w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig1.jpg?resize=300%2C182 300w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig1.jpg?resize=768%2C465 768w\" sizes=\"auto, (max-width: 700px) 100vw, 700px\" \/><figcaption id=\"caption-attachment-2328\" class=\"wp-caption-text\"><strong>Figure 1.<\/strong> A generic molecular sieve capacity decline curves<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Case Study:<\/strong><\/p>\n<p>If your regeneration circuit has excess capacity over the \u201cnormal design conditions\u201d, i.e., a design factor, you have standby time. This excess capacity allows you to reduce your online adsorption time and \u201cturn the beds around\u201d faster by regenerating the beds in a shorter cycle time.\u00a0\u00a0 When you are involved in the design of an adsorption unit, it is recommended to add 10 \u2013 20% excess regeneration capacity.<\/p>\n<p>Because of the capacity decline curves flatten out, available standby time may be able to extend the life of a molecular sieve unit when your unit is operating on fixed cycle times.\u00a0 Other operating options include: running each cycle to water breakthrough; and, reducing the cycle times in discreet steps throughout the life of the adsorbent.<\/p>\n<p>To demonstrate application of the developed program and illustrate the benefits of standby time we considered the same case study as in the May 2015 TOTM [1]. As shown in Figure 2, a natural gas processing plant has commissioned a new 3 tower molecular sieve dehydration unit to process 11.3 x 10<sup>6 <\/sup>std m<sup>3<\/sup>\/d (400 MMscfd) prior to flowing to a deep ethane recovery unit.\u00a0 The unit is expected to run for 3 years before needing a recharge and the plant turnaround is based on this expectation.\u00a0 The following assumptions are made:<\/p>\n<ul>\n<li>A 3 tower system (2 towers on adsorption, 1 on regeneration)<\/li>\n<li>External Insulation<\/li>\n<li>Tower ID = 2.9 m (9.5ft)<\/li>\n<li>Each tower contains 24630 kg (54300 lb<sub>m<\/sub>) of Type 4A 4&#215;8 mesh beads<\/li>\n<li>Regeneration circuit capable of handling an extra 15% of flow<\/li>\n<li>Available standby time 0.5 hour<\/li>\n<li>Unit is operated on fixed time cycles<\/li>\n<li>No step-change events such as liquid carryover, poor flow distribution, etc.<\/li>\n<li>Figure 2. Typical process flow diagram for a 3-tower adsorption dehydration system [3]<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2332\" aria-describedby=\"caption-attachment-2332\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2332\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig2-e1465223883118.png?resize=700%2C440\" alt=\"Figure 2. Typical process flow diagram for a 3-tower adsorption dehydration system [3]\" width=\"700\" height=\"440\" \/><figcaption id=\"caption-attachment-2332\" class=\"wp-caption-text\"><strong>Figure 2.<\/strong> Typical process flow diagram for a 3-tower adsorption dehydration system [3]<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>The design basis and molecular sieve design summary are shown in Tables 1 and 2.\u00a0 The additional 15% of flow from the regeneration gas heater is well below the point at which bed lifting will occur.<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2334\" aria-describedby=\"caption-attachment-2334\" style=\"width: 659px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2334\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table1.jpg?resize=659%2C145\" alt=\"Table 1. Design basis for the case study [1]\" width=\"659\" height=\"145\" srcset=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table1.jpg?w=659 659w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table1.jpg?resize=300%2C66 300w\" sizes=\"auto, (max-width: 659px) 100vw, 659px\" \/><figcaption id=\"caption-attachment-2334\" class=\"wp-caption-text\"><strong>Table 1.<\/strong> Design basis for the case study [1]<\/figcaption><\/figure>\n<figure id=\"attachment_2335\" aria-describedby=\"caption-attachment-2335\" style=\"width: 682px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2335\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table2.jpg?resize=682%2C100\" alt=\" Table 2. Design summary for the case study [1]\" width=\"682\" height=\"100\" srcset=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table2.jpg?w=682 682w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table2.jpg?resize=300%2C44 300w\" sizes=\"auto, (max-width: 682px) 100vw, 682px\" \/><figcaption id=\"caption-attachment-2335\" class=\"wp-caption-text\"><strong>Table 2.<\/strong> Design summary for the case study [1]<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>Using the concepts outlined in chapter 18 of reference [3], the calculated design life factor, L<sub>F<\/sub>, is 0.60 after 3 years (Number Of Cycles, NOC = 1095) of operation at design conditions. This point lies slightly above the \u201caverage\u201d life curve as seen in Figure 3. These calculated values will be presented in the computer output table on the following pages.<\/p>\n<p>After 12 months of operation, a Performance Test Run (PTR) is conducted.\u00a0 The results are shown in Table 3. The feed flow rate and temperature are slightly lower compared to the design values.\u00a0 A water breakthrough time of 20.9 hours is recorded.<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2336\" aria-describedby=\"caption-attachment-2336\" style=\"width: 445px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2336\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table3.jpg?resize=445%2C169\" alt=\" Table 3. Results of Performance Test Run (PTR) after 12 months of operation [1]\" width=\"445\" height=\"169\" srcset=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table3.jpg?w=445 445w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table3.jpg?resize=300%2C114 300w\" sizes=\"auto, (max-width: 445px) 100vw, 445px\" \/><figcaption id=\"caption-attachment-2336\" class=\"wp-caption-text\"><strong>Table 3.<\/strong> Results of Performance Test Run (PTR) after 12 months of operation [1]<\/figcaption><\/figure>\n<figure id=\"attachment_2337\" aria-describedby=\"caption-attachment-2337\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2337\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig3-e1465224937851.jpg?resize=700%2C391\" alt=\"Figure 3. Design condition life factor (LF = 61.0 %) at NOC = 1095\" width=\"700\" height=\"391\" \/><figcaption id=\"caption-attachment-2337\" class=\"wp-caption-text\"><strong>Figure 3.<\/strong> Design condition life factor (LF = 61.0 %) at NOC = 1095<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Tables 4A and 4B present the input data for the developed program (GCAP Option 18F) in SI (System International) and FPS (foot-Pound-Second) systems of units, respectively. The input values for the saturation water content at operation and design conditions by default were zero. Therefore, the program predicted the water content and populated the corresponding input fields. Similarly, the program estimated the gas compressibility factors based on the gas relative density at the operation and design conditions. The program is capable of performing compound bed calculations. In this case study, only one size molecular sieve (MS) was specified; therefore, the mass and density of the second layer of MS are 0. As shown in Table 1, the current adsorption time is 16 hours; therefore, the step (total regeneration) time for this 3-tower system will be 8 hours.<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2338\" aria-describedby=\"caption-attachment-2338\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2338\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table4a-e1465225004659.png?resize=700%2C384\" alt=\"Table 4A. GCAP Option 18F input data for the case study (SI units)\" width=\"700\" height=\"384\" \/><figcaption id=\"caption-attachment-2338\" class=\"wp-caption-text\"><strong>Table 4A.<\/strong> GCAP Option 18F input data for the case study (SI units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2342\" aria-describedby=\"caption-attachment-2342\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2342\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table4b-e1465225285562.png?resize=700%2C377\" alt=\"Table 4B. GCAP Option 18F input data for the case study (FPS units)\" width=\"700\" height=\"377\" \/><figcaption id=\"caption-attachment-2342\" class=\"wp-caption-text\"><strong>Table 4B.<\/strong> GCAP Option 18F input data for the case study (FPS units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Tables 5A and 5B present the GCAP Option 18F numerical results for this case study in SI and FPS systems of units, respectively.<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2343\" aria-describedby=\"caption-attachment-2343\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2343\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table5a-e1465225344826.png?resize=700%2C226\" alt=\"Table 5A. GCAP Option 18F numerical results for the case study (SI units)\" width=\"700\" height=\"226\" \/><figcaption id=\"caption-attachment-2343\" class=\"wp-caption-text\"><strong>Table 5A.<\/strong> GCAP Option 18F numerical results for the case study (SI units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2344\" aria-describedby=\"caption-attachment-2344\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2344\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table5b-e1465225585735.png?resize=700%2C232\" alt=\"Table 5B. GCAP Option 18F numerical results for the case study (FPS units)\" width=\"700\" height=\"232\" \/><figcaption id=\"caption-attachment-2344\" class=\"wp-caption-text\"><strong>Table 5B.<\/strong> GCAP Option 18F numerical results for the case study (FPS units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>The PTR L<sub>F <\/sub>is determined (using the concepts in Chapter 18 [3]) to be 0.675 after 365 cycles (one year of operation). It is important and useful to understand the equation sequence of the concepts in Chapter 18 [3], as shown by Equations 18.5 through 18.10 to arrive at the cited value for LF. This data point is labeled \u201cOP1\u201d (see the legend on top) and shown in Figure 4 and is seen to lie just between the generic \u201cAverage\u201d and \u201cA_G) curves. Based on this data point and the built-in mathematical model, GCAP Option 18F generates a performance curve labeled \u201cOperation\u201d and is shown in Figure 5. Note that the slope of the curves are starting to flatten out. Since the generated PTR curve is lower than the design L<sub>F<\/sub> curve, the molecular sieves will experience water breakthrough if operated at design conditions in less than three years.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2345\" aria-describedby=\"caption-attachment-2345\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2345\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig4-e1465225687291.png?resize=700%2C508\" alt=\"Figure 4. Performance test run (PTR) life factor (LF = 67.5%, NOC = 365)\" width=\"700\" height=\"508\" \/><figcaption id=\"caption-attachment-2345\" class=\"wp-caption-text\"><strong>Figure 4.<\/strong> Performance test run (PTR) life factor (LF = 67.5%, NOC = 365)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2346\" aria-describedby=\"caption-attachment-2346\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2346\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig5-e1465225743541.png?resize=700%2C511\" alt=\"Figure 5. Projected life factor curve passing through PTR data point\" width=\"700\" height=\"511\" \/><figcaption id=\"caption-attachment-2346\" class=\"wp-caption-text\"><strong>Figure 5.<\/strong> Projected life factor curve passing through PTR data point<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Figure 6 shows the projected life factor, L<sub>F<\/sub>, after 3 years (NOC = 1095) of service at design conditions.\u00a0 From the projected curve, F<sub>L<\/sub> =0.556 for NOC = 1095. This data point is labeled \u201cOP2\u201d. If the capacity decline continues to follow the same trend as seen from the PTR curve, water breakthrough will occur after 802 cycles or just a little over 2 years from startup if operation continues at design conditions of L<sub>F<\/sub> = 0.589. This prediction compares favorably to the results of the May 2015 Tip of the Month. This data point is labeled \u201cOP3\u201d and shown in Figure 7.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2347\" aria-describedby=\"caption-attachment-2347\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2347\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig6-e1465225808295.png?resize=700%2C507\" alt=\"Figure 6. Projected life factor at 3 years (NOC = 1095) running at design conditions which gives LF = 55.6 %\" width=\"700\" height=\"507\" \/><figcaption id=\"caption-attachment-2347\" class=\"wp-caption-text\"><strong>Figure 6.<\/strong> Projected life factor at 3 years (NOC = 1095) running at design conditions which gives LF = 55.6 %<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2348\" aria-describedby=\"caption-attachment-2348\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2348\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig7-e1465225866915.png?resize=700%2C508\" alt=\"Figure 7. Projected life factor (LF = 58.9%) running at design conditions which gives NOC = 802\" width=\"700\" height=\"508\" \/><figcaption id=\"caption-attachment-2348\" class=\"wp-caption-text\"><strong>Figure 7.<\/strong> Projected life factor (LF = 58.9%) running at design conditions which gives NOC = 802<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>Because the unit has a regeneration circuit that can handle an additional 15% of flow, the complete regeneration cycle (heating, cooling, de-and re-pressurization and standby) can be reduced from 8.0 hours to 7.0 hours or an adsorption time of 14 hours instead of 16 hours.\u00a0 This allows the beds to turn around faster. Tables 6A and 6B are the same as Tables 4A and 4B with a revealed field to specify the revised adsorption time of 14 hours. Table 7 presents the additional program numerical results for the revised adsorption time of 14 hours.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2352\" aria-describedby=\"caption-attachment-2352\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2352\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table6a-1-e1465228443844.png?resize=700%2C345\" alt=\"Table 6A. GCAP Option 18F input data with the revised adsorption time for the case study (SI units)\" width=\"700\" height=\"345\" \/><figcaption id=\"caption-attachment-2352\" class=\"wp-caption-text\">Table 6A. GCAP Option 18F input data with the revised adsorption time for the case study (SI units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2350\" aria-describedby=\"caption-attachment-2350\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2350\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table6b-e1465226222879.png?resize=700%2C347\" alt=\"Table 6B. GCAP Option 18F input data with the revised adsorption time for the case study (FPS units)\" width=\"700\" height=\"347\" \/><figcaption id=\"caption-attachment-2350\" class=\"wp-caption-text\"><strong>Table 6B.<\/strong> GCAP Option 18F input data with the revised adsorption time for the case study (FPS units)<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2351\" aria-describedby=\"caption-attachment-2351\" style=\"width: 642px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-2351\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table7.png?resize=642%2C95\" alt=\"Table 7. GCAP Option 18F program additional numerical results for the revised adsorption time of 14 hours\" width=\"642\" height=\"95\" srcset=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table7.png?w=642 642w, https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/table7.png?resize=300%2C44 300w\" sizes=\"auto, (max-width: 642px) 100vw, 642px\" \/><figcaption id=\"caption-attachment-2351\" class=\"wp-caption-text\"><strong>Table 7.<\/strong> GCAP Option 18F program additional numerical results for the revised adsorption time of 14 hours<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Using the reduced cycle time (the complete cycle time is now 21 hours vs the original 24 hours), we find an L<sub>F<\/sub> = 0.543.\u00a0 This is because less water is being adsorbed per cycle.\u00a0 This occurs at the 1250 (NOC = 365 + 886.4 = 1251.4) cycles labeled as \u201cROP\u201d and shown in Figure 8 below. \u00a0The May 2015 TOTM was based on visually interpolating the capacity decline curves.\u00a0 That method resulted in an L<sub>F<\/sub> = 0.53 which occurred around the 1500 cycle mark.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_2353\" aria-describedby=\"caption-attachment-2353\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img data-recalc-dims=\"1\" decoding=\"async\" loading=\"lazy\" class=\"wp-image-2353 size-full\" src=\"https:\/\/i0.wp.com\/www.jmcampbell.com\/tip-of-the-month\/wp-content\/uploads\/2016\/06\/fig8-e1465228599145.png?resize=700%2C508\" alt=\"fig8\" width=\"700\" height=\"508\" \/><figcaption id=\"caption-attachment-2353\" class=\"wp-caption-text\"><strong>Figure 8.<\/strong> Projected life factor (LF = 54.3% and NOC = 1251.4) if standby time is used<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>If the plant elects to take advantage of the standby time and operate at reduced cycle time immediately following the PTR, the molecular sieves should last an additional 25.5 months (2.13 years), resulting in a total life of 3.12 years (the May 2015 TOTM methodology predicted a total life of 3.7 years).\u00a0\u00a0 In this case, standby time will allow the unit to operate until the scheduled plant turnaround.<\/p>\n<p>The different estimates of total life between the two methods is due to the flattening out of the decay curves.\u00a0 Very small changes in L<sub>F<\/sub> result in large differences in total number of cycles.\u00a0 There is inherent uncertainty in taking a data point from a curve using visual interpolation. GCAP eliminates this uncertainty.<\/p>\n<p>For units where the estimation of total life is critical, it is recommended to run another PTR. For the Case Study under evaluation, this should occur approximately one year after the first PTR.<strong>\u00a0<\/strong><\/p>\n<p>A free copy of the <a href=\"https:\/\/petroskills.com\/products\/training#gcap\">GCAP program <\/a>can be obtained by attending PetroSkills &#8211; John M Campbell <a href=\"http:\/\/petroskills.com\/course\/g4\"><strong>G4 (<\/strong>Gas Conditioning and Processing<strong>)<\/strong><\/a> course.<\/p>\n<p>The approach discussed in this Tip of the Month should help a facility engineer plan for the inevitable replacement of molecular sieves in their natural gas dehydration facility.<\/p>\n<p>To learn more about similar cases and how to minimize operational problems, we suggest attending our <a href=\"http:\/\/petroskills.com\/course\/g4\"><strong>G4 (<\/strong>Gas Conditioning and Processing<strong>)<\/strong><\/a><strong><u>,<\/u><\/strong> <a href=\"http:\/\/petroskills.com\/course\/g5\"><strong>G5 (<\/strong>Advanced Applications in Gas Processing<strong>)<\/strong><\/a><strong>,<\/strong> and <a href=\"http:\/\/petroskills.com\/course\/pf4\">PF4 (Oil Production and Processing Facilities)<\/a> courses.<\/p>\n<p><em>PetroSkills <\/em>offers consulting expertise on this subject and many others. For more information about these services, visit our website at <a href=\"http:\/\/petroskills.com\/consulting\">http:\/\/petroskills.com\/consulting<\/a>, or email us at <a href=\"mailto:consulting@PetroSkills.com\">consulting@PetroSkills.com<\/a>.<\/p>\n<p><em>\u00a0<\/em><\/p>\n<p><em>By: Mahmood Moshfeghian and Harvey M. Malino<\/em><\/p>\n<p>&nbsp;<\/p>\n<p>References:<\/p>\n<ol>\n<li>Malino, H.M., <a href=\"http:\/\/www.jmcampbell.com\/tip-of-the-month\/2014\/12\/troubleshooting-gas-liquid-separators-removal-of-liquids-from-the-gas\/\">May 2015 tip of the month<\/a>, PetroSkills \u2013 John M. Campbell, 2015<\/li>\n<li>GCAP 9.2.1 Software, PetroSkills \u2013 John M Campbell \u201cGas Conditioning and Processing Computer Program,\u201d Editor Moshfeghian, M., PetroSkills, Katy, Texas, 2016.<\/li>\n<li>Campbell, J.M., \u201cGas Conditioning and Processing, Volume 2: The Equipment Modules,\u201d 9<sup>th<\/sup> Edition, 2<sup>nd<\/sup> Printing, Editors Hubbard, R. and Snow\u2013McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>The May 2015 tip of the month (TOTM) [1] presented a method which allows the users to estimate the decline of their adsorbent based on only one performance test run (PTR) for molecular sieve dehydrators using low pressure regeneration. This permits early formulation of a credible action plan. Site-specific factors will determines an adsorption unit\u2019s [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[],"coauthors":[17],"class_list":["post-2327","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p1pQc4-Bx","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2327","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/comments?post=2327"}],"version-history":[{"count":8,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2327\/revisions"}],"predecessor-version":[{"id":2354,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2327\/revisions\/2354"}],"wp:attachment":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/media?parent=2327"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/categories?post=2327"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/tags?post=2327"},{"taxonomy":"author","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/coauthors?post=2327"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}