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Title: Projected Number O&G Wells Combined for MT, ND, SD, WY
Author: Richard Sojda
Comments: PROJECTED NUMBER OF O&G WELLS FOR MT, ND, SD, WY BASED ON BLM'S RFD.
Notes for Converting BLM’s Reasonable Foreseeable Future Projections for Oil and Gas Wells into Standardized Numerical Categories: MT, ND, SD, WY
Richard S. Sojda
26 May 2014
1. Spatial data for WY and SD was provided via email by Cathy Stilwell, GIS Specialist, BLM, Casper, WY
2. Spatial data for MT – HiLine was obtained from: http://www.blm.gov/mt/st/en/fo/malta_field_office/rmp/hiline_rmp/gis_maps.html
3. Spatial Data for MT – Dillon was provided via email by Laurie Blinn, GIS Specialist, BLM, Dillon, MT
4. Spatial data for MT - Miles City was obtained from:
http://www.blm.gov/mt/st/en/fo/miles_city_field_office/rmp/draft_rmp/miles_city_draft_rmp.html
5. Attribute table data were examined from the BLM Development Potential spatial data layers. The column labels differed among Field Office’s (e.g, “potential”, “devpot”, “development”, etc.)
a. The non-quantified categories included: VERY HIGH, HIGH, MODERATE, LOW, NONE, NEGLIGIBLE, NOT ASSESSED.
b. Different offices examined oil separate from gas; others combined the projection.
c. The attribute tables contained non-quantified categories for the following FO/Districts/RMPs: Dillon, South Dakota, HiLine, Big Horn Basin, Casper, Kemmerer, Lander, Pinedale, and Rawlins. However, sometimes oil categories were not quantified, sometimes gas were not, sometimes the combined were not.
d. When numerical categories were provided, they were presented as ranges, e.g., 5-20 wells per township. Numerical categories were not the same among offices, nor between oil and gas.
e. Any areas classified as “Not Assessed” were given the value of “0” since they represent areas off-limits to oil and gas development, such as wilderness areas.
f. Dean Stilwell, BLM Casper, WY, provided midpoints for categories that he developed for the BLM as an attachment to an email on 22 May 2014 [StilwellEdits_DRAFT_notes_standardizing_RFD_categories_v2.docx].
6. Notes where decisions on categories were made are highlighted in bright green. Sometimes these decisions were arbitrary, but are so noted.
7. When categories overlapped, e.g., 2-10 and 10-20, midpoints were calculated by starting the higher category with the next higher number. In this example, 2-10 and 11-20.
8. Non-quantified categories in the attribute tables of the spatial data were quantified when possible as follows.
MT/ND/SD:
BILLINGS:
No spatial data as of 30 April 2014
DILLON:
Oil & Gas Combined (Conventional and CBNG):
Laurie Blinn, BLM informed me that these categories were based on geological expert opinion and were never quantified
HILINE:
Oil & Gas Conventional:
http://www.blm.gov/pgdata/etc/medialib/blm/mt/field_offices/malta/rmp/docs.Par.96769.File.dat/HiLine_OilGasRFD.pdf ,
From Page 68
High: 54
Moderate: 70 [Note: might High and Moderate be reversed?]
Low:
Very Low:
From Page 77 [These are the ones used.]:
High: 110
Moderate: 60
Low: 11
Very Low: 0.5
CBNG:
From Page 78:
Very Low: 0.5
NOTE: The 2013 data provided appeared to be for both Conventional Oil & Gas and CGNG combined, as there was no distinction in the attribute table, and was treated that way. However, in the RFD, a category was provided for CBNG and that was Very Low = 0.5. Therefore, the combined values assigned were the Conventional Oil & Gas for all categories except Very Low, for which the two numbers were added to get 1.0.
LEWISTOWN:
No spatial data as of 30 April 2014
MILES CITY:
Oil & Gas Combined (Conventional and CBNG):
BLM gave me the numeric equivalent for the categories
High: 6 10
Moderate: 3 - 5
Low: 1 - 2
NORTH DAKOTA:
No spatial data as of 30 April 2014
RFD is only in the preparation stage and not available
SOUTH DAKOTA:
Oil & Gas Combined (Conventional and CBNG) :
http://www.blm.gov/pgdata/etc/medialib/blm/mt/field_offices/south_dakota/rmp/rfd.Par.36496.File.dat/T_4.pdf
Accessed 28 April 2014
High: 15
Moderate: 6
Low: 1.5
Very Low: 0.5
None: 0
Although the RFD document lists 5 categories, the spatial data only use 3: High, Moderate, and Low; so, only those three were used and populated with the values above.
WY:
BIG HORN BASIN:
http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/bighorn/docs/rfds.Par.94367.File.dat/OilandGas.pdf
Accessed 28 April 2014
Oil & Gas Conventional: PAGE 75:
High: 100+wells This category was not used in the spatial data.
Moderate: 20 to 100 wells
Low:
2 to 100
High: 41-100
Moderate: 21-40
Low: 11-20
Very Low: 2 – 10
None: 0
Negligible: 1 [This number was based on no category being provided between 0 and 2]
CGNG (range):
Very High: >220
High: 71 - 220
Moderate: 21 - 70
Low: 5 - 20
Very Low: 0 - 4
None: 0
Negligible: ? [0.5 was arbitrarily used since categories did not leave anything arithmetically for this category)
Point Estimates: http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/buffalo/docs/rfd.Par.48552.File.dat/FinalBFORFD_2012.pdf
Accessed 29 April 2014
Oil & Gas Conventional (point) [Table 5]:
Very High: 129
High: 70
Moderate: 30
Low: 15
Very Low: 6
None: 0
Negligible: 0.5
CBNG (point) [Table 6]:
Very High: >220
High: 71 - 220
Moderate: 21 - 70
Low: 6 - 20
Very Low: 1 - 5
None: 0
CASPER:
http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/casper/docs.Par.27322.File.dat/03_rfd.pdf [Table 14]
Accessed 29 April 2014
Oil & Gas Conventional:
High: 110
Moderate: 60
Low: 11
Very Low: 1
CBNG:
High: 144
Moderate: 60
Low: 11
Very low: 1
KEMMERER:
Oil & Gas Conventional: [http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/kemmerer/docs.Par.62020.File.dat/05_rfd.pdf]
Accessed 29 April 2014
High: >100
Moderate: 21 - 100
Low: 0 - 20
CBNG [the following are from the attribute table for CBNG]:
Moderate: 20 – 100
Low: 10 – 19
Very Low: 0 – 9
None: 0
LANDER:
Oil & Gas Conventional:
http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/lander/rfds/oil_gas.Par.73745.File.dat/Table08_developmentpotential.pdf
Accessed 29 April 2014
High: 110
Moderate: 60
Low: 10
Very Low: 0.25
None: 0
CBNG: http://www.blm.gov/pgdata/etc/medialib/blm/wy/programs/planning/rmps/lander/rfds/oil_gas.Par.57928.File.dat/Table09_cbngpotential.pdf
Accessed 29 April 2014
High: 110 This category was not used in the spatial data.
Moderate: 60
Low: 8
Very Low: 0.25
None: 0
NEWCASTLE:
Oil & Gas Conventional [The following are from the attribute table for conventional O&G, and from the legend of a digital map (NFO_ConventionalPotential_Dec2010.pdf) provided by Dean Stilwell, BLM, Casper, WY on 29 April 2014]:
Very High: >30
High: 21 - 30 [not used in attribute table]
Moderate: 10 - 20
Low: 1 - 9
Very Low: 150
High: 50 – 149
Moderate: 20 – 49
Low: 5 – 19
Very Low: 1 -5
None: 0
CBNG:
Moderate: 10 - 30
Low: 2 - 10
Very Low: 1
None: 0
9. Thoughts on developing an algorithm for assigning a numerical attribute to each township for total number of wells projected:
a. One column was added to each attribute table: PotMidxxxx, plus the suffix “GBNG”, “Conv” or “Comb”, as appropriate, corresponding to the point estimate/ midpoint value of the range, when provided.
b. All non-quantified categories, e.g., Very High, High, Moderate, Low, Very Low, and None (including Not Assessed) will be converted for both Conventional Oil and Gas, CBNG, and Oil and Gas Combined using all three columns. For areas where no quantification was done (e.g., Dillon), the columns will remain empty.
c. PotMid: The only common value among areas is the midpoint/ point estimate, and where ranges of estimates are provided, the midpoint will be used. For the first attempt at additional analysis, only the midpoint will be used. At a later stage similar columns will be considered for inclusion as the Maximum and Minimum estimates. However, these data are sparse across all geography.
d. The maximum category is often presented as an inequality, e.g., >100, and the next lower category as X to 100. Therefore, the maximum category was assigned the next highest number. In this example, the value assigned would be 101.
e. For areas with separate estimates for Conventional and CBNG, the estimate for a township will be summed.
f. All townships will be merged.
g. Various algorithms for categorization in ArcGIS will be examined for categorizing the data, including natural breakpoints, six uniform/equal categories, and others.
h. Categories will be symbolized at the township scale. We recognize that all townships are not of equal size for at least three reasons: (1) inaccuracies in base spatial CadNSDI (PLSS) data, (2) political boundary conditions, and (3) survey correction lines. For our first iteration of the analysis, we will simply ignore these problems and not attempt to normalize slivers, polygons of zero size, and townships of unequal size by area or other characteristic.
10. Colour Scheme used to symbolize the non-numeric categories, using colours that seemed to work well for my level of colour-blindness:
Non-numeric Category Coulour Name (ArcGIS) Column-Row in Colour Table
Very High Mars Red 2 – 3
High Fire Red 3 - 3
Moderate Seville Orange 4 - 4
Low Quetzel Green 7 – 4
Very Low Solar Yellow 5 - 3
Negligible Topaz Sand 4 - 1
None Moorea Blue 10 - 4
Not Assessed Sugilite Sky 10 – 1
11. This is the step-by-step procedure used for adding the midpoint values to the attribute tables in ArcMap 10.2.1. This was only needed to be used (primarily in Montana) when the attribute table had multiple rows (polygons). When there were few rows (polygons), the new midpoint values could be added directly, replacing steps e – g.
a. Layers were renamed to begin with the prefix “LCC”. These are copies of the original data files for which the new PotMidxxxx columns had been added to the attribute files.
b. Open attribute table
c. Add field (PotMidxxxx)
d. Start editor
e. Select attributes based on the RFD category, e.g., “High”
f. Apply “Field Calculator” on the new field, populating the new field for the selected categories with the numeric value as described above and listed in the corresponding excel file, RFD_categories_vX.xlsx
g. Clear the selection
h. Save edits
i. Stop editing
j. Close the attribute table
k. Repeat steps e – i for each category
l. Save the .mxd
m. Repeat steps b – k for each layer
12. This is the procedure for completing the Wyoming map of Combined Conventional Oil & Gas and CBNG projected well densities. Similar step-by-step procedures were used as in #11, above, but not delineated here for simplicity.
a. All individual Field Office spatial data were merged for Conventional Oil & Gas [LCCWYmerged_ConvPotentials]
b. All individual Field Office spatial data were merged for CBNG [LCCWYmerged_CBNGPotentials]
c. LCCWYmerged_ConvPotentials and LCCWYmerged_CBNGPotentials were combined using the Union procedure [LCCWYmerged_CombPotentials]
d. A field was added to that attribute table [PotMidComb] and the field calculator was used to populate the field by adding the two fields PotMidConv and PotMidCBNG.
e. PotMidComb was symbolized to make a map depicting the “BLM's Projected Number of Conventional O&G and CBNG Wells Per Township in Wyoming”. See # 13, below.
13. Colour Scheme used to symbolize the numeric categories, using colours that seemed to work well for my level of colour-blindness:
Numeric Category Coulour Name (ArcGIS) Column-Row in Colour Table
0 Moorea Blue 9 - 4
0.000001 - 35 Solar Yellow 5 - 3
35. 000001 – 70.5 Yucca Yellow 5 - 1
70.500001 - 144 Electron Gold 4 - 3
144. 000001 - 330 Flame Red 3 - 4
330. 000001 - 2515 Tuscan Red 2 - 5
14. The following process was used to provide an assessment of road density in Montana:
a. Downloaded data for MT roads from openstreetmap.org on 23 June 1014
b. These data were projected to NAD1983 Albers
c. They were then clipped for MT to remove minor lines that crossed the state border
d. Road length was calculated in the attribute table using calculate geometry
e. The previously obtained CadNSDI data were projected to NAD1983 Albers
f. A spatial join was done with LCC_MT_roads_NAD1983albers_clip and LCC_MT_CadNSDI_clip_NAD1983Albers
g. In the attribute table for LCC_MT_CadNSDI_roads_spatialjoin, PLSSID was summarized by roadlength
h. A field, RdDensity, was added to the table and calculated as: roadlength / SqMi to account for slightly different sizes of townships and for “sliver” townships.
i. RdDensity was then symbolized with ten equal categories.
j. The attribute table was exported as a text file to ../spatial_data/roads_OGexist
15. The following process was used to provide an assessment of oil well density in Montana:
a. A spatial join was done with MT_OilGas_Wells_existing_BLM_data and LCC_MT_CadNSDI_clip_NAD1983Albers
b. In the attribute table for LCC_MT_CadNSDI_ExistWells_spatialjoin, PLSSID was summarized by Join_Count
c. A field, WellDensity, was added to the table and calculated as: Join_Count / SqMi to account for slightly different sizes of townships and for “sliver” townships.
d. Well_Density was then symbolized with ten categories using Natural Break (Jenks).
e. The attribute table was exported as a text file to ../spatial_data/roads_OGexist
16. In October 2014, I received new RFD data from Cathy Stilwell, BLM – Casper, all FOs in WY, and for ND, SD, and Malta and Lewistown in MT. A field, MidPoint, is provided that I was told by Dean Stilwell, BLM – Casper, that is not necessarily the arithmetic midpoint, but rather is his expert opinion as to what is the most likely scenario within the range given in the RFD.
a. National_CONV_WithMidPointsOctober2014 and National_CBNG_WithMidPointsOctober2014 were combined using the Union procedure [National_COMB_WithMidPointsOctober2014]
b. A field, MidPtCOMB was added to the attribute table of National_COMB_WithMidPointsOctober2014. The field calculator was then used to add the two midpoints from the CONV and CBNG layers to populate MidPtCOMB, and then this field was used to symbolize the map based on 10 categories with the lowest category forced to be “0”.
c. This mxd is: OG_all-BLM-2014-10-1_v1.mxd
Subject: Number CBNG andConventional O&G wells combined per township as projected in BLM's Reasonable Foreseeable Development (RFD) analysis.
Category:
Keywords: Oil and Gas wells; MT; ND; SD; WY
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