{"id":2402,"date":"2016-10-04T15:56:12","date_gmt":"2016-10-04T20:56:12","guid":{"rendered":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/?p=2402"},"modified":"2016-10-04T16:00:04","modified_gmt":"2016-10-04T21:00:04","slug":"estimating-methanol-removal-in-the-gas-sweeting-process","status":"publish","type":"post","link":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/2016\/10\/estimating-methanol-removal-in-the-gas-sweeting-process\/","title":{"rendered":"Estimating Methanol Removal in the Gas Sweeting Process"},"content":{"rendered":"

Charts and Correlations for Estimating Methanol Removal in the <\/em><\/strong>Gas Sweetening Process<\/em><\/strong><\/p>\n

 <\/p>\n

The gas-sweetening process by amines like methyldiethanolamine (MDEA) removes a considerable amount of methanol from a sour gas stream. Moreover, if the methanol content of the sour gas is high, the sweet gas may still retain high methanol content and can cause operational troubles in the downstream processes. Provisions of purging reflux (Water Draw) of the regenerator column and its replacement with \u201cFresh Water\u201d can improve methanol recovery [1, 2].<\/p>\n

 <\/p>\n

The July 2016 tip of the month<\/a> (TOTM) considered the presence of methanol in the sour gas stream and determined the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams [2]. It simulated a simplified MDEA gas-sweetening unit by computer and studied the effect of sour gas methanol content, and the rate of replacing condensed reflux with fresh water on the sweet gas methanol content. For the sour gas temperature of 43.3 and 32.2 \u00b0C (110 and 90 \u00b0F) the tip studied three inlet gas methanol contents of 50, 250, and 500 PPM on mole basis. In each case the tip varied the rate of fresh water replacement from 0 to 100 % by an increment of 20%.<\/p>\n

 <\/p>\n

The methanol removal efficiency (MRE) on the volume basis is defined by:<\/p>\n

\"eq\"<\/p>\n

 <\/p>\n

Table 1 presents the summary of calculated methanol removal efficiency (MRE) based on the simulation results of the July 2016 TOTM [2].<\/p>\n

 <\/p>\n

\"Table
Table 1. The effect of purging and sour gas temperature on methanol removal efficiency [2]<\/figcaption><\/figure>\n

 <\/p>\n

In continuation of the July 2016 TOTM, this tip will consider the presence of methanol in the sour gas stream and determine the quantitative traces of methanol ending up in the sweet gas, flash gas and acid gas streams. This tip simulates a simplified MDEA gas-sweetening unit by computer simulation [3, 4]. This tip also studies the effect of sour gas methanol content, temperature and the rate of replacing condensed reflux with fresh water on the sweet gas methanol content.<\/p>\n

 <\/p>\n

For the sour gas temperatures of 43.3, 32.2 and 21.1 \u00b0C (110, 90, and 70 \u00b0F) the tip studies three inlet sour gas methanol contents of 50, 250, 500 PPM on mole basis. In each case the tip varies the rate of fresh water replacement from 0 to 100 % by an increment of 20%. Similar to the September 2016 TOTM<\/a> [5] and based on the computer simulation results, the tip develops simple charts and correlations to estimate the methanol removal efficiency under various operating conditions. These charts and correlations are accurate enough for facilities calculations.<\/p>\n

 <\/p>\n

\u00a0<\/strong><\/p>\n

Case Study:<\/strong><\/p>\n

For the purpose of illustration, this tip considers sweetening of a sour gas stream saturated with water using the basic and modified MDEA processes as described in the July 2016 TOTM [2]. In addition to the two sour gas temperatures reported in the July TOTM, this tip also considers a sour gas temperature of 21.1 \u00b0C (70 \u00b0F). Table 2 presents its composition on the dry basis, gas standard volume rate, pressure, and temperatures. This tip uses ProMax [6] simulation software with the \u201cAmine Sweetening \u2013 PR\u201d property package to perform all of the simulations.<\/p>\n

 <\/p>\n

 <\/p>\n

Results and Discussions:<\/strong><\/p>\n

Figures 1 through 3 present the calculated MRE as a function of the reflux rate replacement (RRR) with fresh water for the sour gas temperatures of 43.3, 32.2, and 21.1 \u00b0C (110, 90, and 70 \u00b0F), respectively. Each figure presents MRE vs replacement rate for the three sour gas methanol contents (50, 250, and 500 PPMV).<\/p>\n

 <\/p>\n

\"Table
Table 2. Feed composition on the dry basis, volumetric flow rate and conditions [2]<\/figcaption><\/figure>\n
\"Figure
Figure 1. Methanol removal efficiency vs reflux replacement for sour gas temperature of 43.3 \u00b0C (110 \u00b0F)<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

\"Figure
Figure 2. Methanol removal efficiency vs reflux replacement for sour gas temperature of 32.2 \u00b0C (90 \u00b0F)<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

\"Figure
Figure 3. Methanol removal efficiency vs reflux replacement for sour gas temperature of 21.1 \u00b0C (70 \u00b0F)<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

Since the three curves for different sour gas methanol contents on each figure are close, the effect of the sour gas methanol content on MRE can be neglected. For each sour gas temperature, the calculated arithmetic average of MRE of the three sour gas methanol content are provided in Figure 4. This figure indicates that as the sour gas temperatures decreases the impact of the reflux rate replacement with fresh water diminishes.<\/p>\n

 <\/p>\n

\"Figure
Figure 4. Average methanol removal efficiency vs reflux replacement<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

A non-linear regression program was used to determine the parameters of the following correlation for the methanol removal efficiency as a function of the reflux rate replacement % (RRR).<\/p>\n

 <\/p>\n

\"eq1\"<\/p>\n

 <\/p>\n

Where:<\/p>\n

MRE = Methanol Removal Efficiency on the mole basis, %<\/p>\n

RRR = Reflux Rate Replacement %<\/p>\n

 <\/p>\n

Table 3 presents the regressed parameters of A, B and C of Equation 1 for the three considered sour gas temperatures. The last two rows in Table 3 present the Average Absolute Percent Error (AAPE) and the Maximum Absolute Percent Error (MAPE), respectively.<\/p>\n

 <\/p>\n

A generalized form of this correlation to cover the temperature effect can be expressed as:<\/p>\n

 <\/p>\n

\"eq2\"<\/p>\n

 <\/p>\n

Where:<\/p>\n

MRE\u00a0\u00a0 = Methanol removal efficiency on the weight basis<\/p>\n

RRR\u00a0\u00a0 \u00a0= Reflux Rate Replacement %<\/p>\n

T\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 = Temperature, \u00baC (\u00baF)<\/p>\n

 <\/p>\n

Table 4 presents the regressed parameters of A1<\/sub>, A2<\/sub>, B1<\/sub>, B2<\/sub>, C1<\/sub> and C2<\/sub> of Equation 2 for temperatures in \u00b0C and \u00b0F. Similarly, the last two rows in Table 4 present the AAPE and the MAPE, respectively.<\/p>\n

 <\/p>\n

\"Table
Table 3. Parameters of Equation 1 for methanol removal efficiency<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

\"Table
Table 4. Parameters of Equation 1 for methanol removal efficiency<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

The MRE predictions by Equation 2 were added to Figure 4 and is presented as Figure 5. In this figure the solid lines present the MRE prediction by Equation 2 and dashed lines with the filled symbols represents simulation results. The analysis of Figures 5 and the calculated values of AAPE and MAPE in Table 4 indicate that accuracy of the proposed correlations, compared to the simulation results, is very good for estimation of methanol removal efficiency (MRE).<\/p>\n

 <\/p>\n

\"fig5\"
Figure 5. Comparison of model prediction of average methanol removal efficiency vs reflux replacement<\/figcaption><\/figure>\n

 <\/p>\n

 <\/p>\n

Conclusions:<\/strong><\/p>\n

Based on the results obtained for the considered case study, this TOTM presents the following conclusions:<\/p>\n

    \n
  1. The impact of the sour gas methanol content on the methanol removal efficiency is small (Figures 1-3), overall only a minor impact, less than 0.5 % point.<\/li>\n
  2. As the sour gas temperature decreases, the methanol removal efficiency increases (Figures 1-5), overall only minor impact, less than 3 % points.<\/li>\n
  3. Methanol removal efficiency with MDEA sweetening can remove only 89-97% of the methanol in the sour gas feed. \u00a0This may still leave more methanol than the gas spec allows. \u00a0A separate water wash step may be required. \u00a0The fresh water used for the water wash could be recycled as\u00a0MDEA reflux purge make-up.<\/li>\n
  4. The tip presents three simple charts (Figures 1-3) and two correlations (Equations 1 and 2) along with their parameters (Tables 3 and 4) for estimating the average methanol removal efficiencies for the sour gas temperatures of 43.3, 32.2, and 21.1 \u00b0C (110, 90, and 70 \u00b0F), respectively.<\/li>\n
  5. Compared to the rigorous computer simulation, the accuracy of the proposed correlations (Equations 1 and 2) to estimate the average methanol removal efficiency is very good (Tables 3 and 4 and Figure 5) and can be used for facilities calculations.<\/li>\n
  6. The proposed correlations (Equations 1 and 2) and charts (Figures 4-5) are easy to use.<\/li>\n<\/ol>\n

    To learn more about similar cases and how to minimize operational troubles, we suggest attending our G6<\/u><\/strong> (Gas Treating and Sulfur Recovery),<\/strong><\/u> G4 (<\/strong>Gas Conditioning and Processing)<\/strong><\/a>,<\/u><\/strong> G5 (<\/strong>Advanced Applications in Gas Processing)<\/strong><\/a>,<\/strong> and PF4<\/u><\/strong> (Oil Production and Processing Facilities)<\/u> courses.<\/p>\n

    PetroSkills | Campbell <\/em>offers consulting expertise on this subject and many others. For more information about these services, visit our website at http:\/\/petroskills.com\/consulting<\/a>, or email us at consulting@PetroSkills.com<\/a>.<\/p>\n

    \u00a0<\/em><\/p>\n

    By: Dr. Mahmood Moshfeghian<\/em><\/p>\n

     <\/p>\n

     <\/p>\n

     <\/p>\n

    References:<\/p>\n

      \n
    1. O\u2019Brien, D., Mejorada, J., Addington, L., \u201cAdjusting Gas Treatment Strategies to Resolve Methanol Issues,\u201d Proceedings of Lawrence Reid Gas Conditioning Conference, Norman, Oklahoma, 2016.<\/li>\n
    2. Moshfeghian, M., July 2016 tip of the month<\/a>, PetroSkills | John M. Campbell, 2016.<\/li>\n
    3. Maddox, R.N., and Morgan, D.J., Gas Conditioning and Processing, Volume 4: Gas treating and sulfur Recovery, Campbell Petroleum Series, Norman, Oklahoma, 1998.<\/li>\n
    4. Campbell, J.M., Gas Conditioning and Processing, Volume 2: The Equipment Modules, 9th<\/sup> Edition, 1st<\/sup> Printing, Editors Hubbard, R. and Snow \u2013McGregor, K., Campbell Petroleum Series, Norman, Oklahoma, 2014.<\/li>\n
    5. Moshfeghian, M., September 2016 tip of the month<\/a>, PetroSkills | John M. Campbell, 2016.<\/li>\n
    6. ProMax 4.0, Bryan Research and Engineering, Inc., Bryan, Texas, 2016.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      Charts and Correlations for Estimating Methanol Removal in the Gas Sweetening Process   The gas-sweetening process by amines like methyldiethanolamine (MDEA) removes a considerable amount of methanol from a sour gas stream. Moreover, if the methanol content of the sour gas is high, the sweet gas may still retain high methanol content and can cause […]<\/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-2402","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p1pQc4-CK","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2402","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=2402"}],"version-history":[{"count":2,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2402\/revisions"}],"predecessor-version":[{"id":2417,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/posts\/2402\/revisions\/2417"}],"wp:attachment":[{"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/media?parent=2402"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/categories?post=2402"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/tags?post=2402"},{"taxonomy":"author","embeddable":true,"href":"http:\/\/www.jmcampbell.com\/tip-of-the-month\/wp-json\/wp\/v2\/coauthors?post=2402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}