This article reviews features available in IHS Piper that can be used to test optimization scenarios for hydrocarbon gathering systems, specifically focusing on compression. General field optimization ideas and workflows are reviewed in a previous blog titled "Field Optimization Using IHS Piper - Part I: Optimizing Gathering Systems". You may want to visit that post prior to reviewing this one. Another earlier post called "Field Optimization Using IHS Piper - Part II: Cost Cutting by Shutting in Wells may also be of interest.

Improving the profitability of a gathering system is typically approached through increased production by drilling additional wells or optimizing production from existing wells. An additional consideration that needs to be addressed is compression optimizations. For example, you could centralize compression, or decommission compressors that are no longer required in a declining field. In Figure 1 the Base Case condition is shown with three compressors providing service to three individual groups of wells and a fourth group of wells are located on the downstream side of the compression. A well uplift potential map is displayed on the GIS view with small bubbles, and the larger bubbles indicate well drawdown.

Figure 1: Base case showing wells with low drawdown (large green well drawdown bubbles = 37.5-50% drawdown) and uplift potential (small light green well uplift bubbles = 1.8 - 2.6 10³m³/d). Note that the wells with uplift potential and lower drawdowns, surrounded by a black polygon above, are not affected by the three compressors in the field (labelled with light grey annotations.

This diagnostic well uplift bubble map highlights areas that have the potential for increased production, and help you focus on areas where adding compression capability will have the greatest impact. The well uplift map in the Base Case was used to select a site for added compression. The model is then used to predict operating conditions which can be achieved by consolidating the three individual compressor stations into a single station serving all four well groups.

Figure 2: Field scenario showing three compressors relocated to a single compressor station downstream of all the wells. Large grey bubbles indicate the previous individual compressor locations. The large green bubble indicates the new location for a compressor battery made up of the three field compressors. Note that all the wells now have drawdowns in the range of 62.5 - 75%, including those surrounded by the black polygon. The drawdown for wells inside the black polygon has been increased (small orange bubbles), and the uplift has been reduced (smaller blue bubbles).

Using the Forecast view for the Base Case (Figure 3) and scenario model (Figure 4) we can compare the total field production.

Figure 3: Total delivery rates for base case over a 12 month forecast.

Figure 4: Total delivery rates for compressor relocation scenario over a 12 month forecast.

Total field production in the scenario with relocated and combined compression is higher than the Base Case, which is expected. With more optimal compression location, all the wells shown 'see' compression and uplift potential for additional wells can be capitalized upon. The well drawdown map can also be used highlight areas where compression can be removed without adverse effects. If the drawdown on wells is very high, operational issues like sanding can occur which have an inherent mitigation cost associated. Reducing the drawdown on these wells can reduce operating costs.

As field production declines over time, compression capacity requirements may be reduced. You may want to test if compressors can be operated at a lower capacity, relocated to more optimal locations, or even decommissioned, to reduce expenditures with low impact on total field deliverability. Create scenarios where compressors have reduced capacity, are placed in alternate locations or are decommissioned. In these scenarios, you will want to know how much operating expenses will be reduced, and how revenues will change as compared to the Base Case. The economics feature in IHS Piper can be used to make a Net Present Value report and Cash Flow report. These reports are available both for the field as well as by facility.

Moving or decommissioning compression may have operational impacts. Using diagnostic maps like the Turner Critical Velocity, Delta Pressure, Hydrostatic Pressure Loss and Liquid Holdup will highlight any adverse consequences of modifying field compression.

Figure 5: Base case model with delta pressure loss map for pipelines. The three field compressors are in their original locations. Note pipelines to the west are showing some moderate pressures losses (138 - 172 kPa(a)), colored yellow.

Figure 6: Compressor scenario with a delta pressure loss map for pipelines shown. Note the pipelines to the west that showed moderate pressure losses in the base case show reduced pressure losses in this scenario.

Depending upon the results, consider testing additional scenarios, or modifying scenarios you have already created. Compressors may not need to run at full capacity to maintain production due to decreased overall rates. If you have multiple compressor units operating in parallel service, you may be able to take a compressor off line, decommission it, or move it to another location without impacting wells that are still on production.

When testing the practicality and feasibility of an alternate scenario you should consider the economic impact of changes, both indirect and direct. Also consider any contractual obligations that might be impacted, operational issues that might arise if you pursue an alternate configuration, and long term field deliverability. Finally, consider if you are primarily concerned with reducing expenditures in the short term, or are looking for opportunities to optimize production. Maybe infrastructure spending will result in substantial production increases? While you would have to invest up front, the long term returns may be well worth that investment. Optimizing the location of compression would require investment, but may have a significant impact of well deliverability.

For further reference:

http://blog.ihs.com/rpe-a-recipe-for-reliable-gathering-system-modeling
https://ihsmarkit.com/products/oil-gas-training-videos.html

One Petro - SPE No. 75946 "Case Study: Including the Effects of Stagnant Water in Gas Gathering System Modeling" by James Young, Ralph McNeil, Jeffery Knibbs

"An Effective Method for Modeling Non-Moving Stagnant Liquid Columns in Gas Gathering Systems" by R.G. McNeil, D.R. Lillico

Tracy Brenner, Principal Analyst/Researcher, IHS Markit Engineering

This article was published by S&P Global Commodity Insights and not by S&P Global Ratings, which is a separately managed division of S&P Global.