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September 2015
Evaluate Leasing Activity with DI Analytics
Under the U.S. model of private mineral ownership,
age associated with a leased tract is a laborious and
complex leasing rules and difficulties with procuring
tricky task.
pertinent courthouse filings make it burdensome to derive mineral ownership. To overcome some of these obstacles, the Drillinginfo Analytics team employs an innovative spatial model to remove duplicate leases and
ascertain leasehold position by grantee.1 The Analytics
team uses a second spatial model to assign grantee
leaseholds to operators, where possible, based on well
ownership.
Introduction
In order to evaluate a potential investment and acquire
the appropriate legal rights to
develop a field, an operator or
investor must have a clear understanding of the exact acreage associated with a lease.
There are many complexities
Second, the original lease grantee may later assign
the lease to someone else, called an assignee. Compiling lease records for a specific operator as the grantee will therefore exclude leases where a third party
grantee assigned the lease to the operator, and these
assignments may represent a significant portion of an
operator’s leasehold position.
The first problem over-states
“...the Drillinginfo
Analytics team employs
an innovative spatial
model to remove
duplicate leases and
ascertain leasehold
position by grantee.”
product addresses two primary problems:
lease, and the second problem
obscures who is the current
owner of a lease. The Analytics team overcomes the first
problem by removing the duplicate lease records through
a spatial mapping of the lease
polygons. We then mitigate the
second problem by assigning
with leasing data, and the
Drillinginfo Analytics leasing
the acreage associated with a
the leases to operators based
on majority well ownership. This approach has limitations, such as the situation where an operator acquires
First, a mineral lease may involve numerous parties
leases from another operator who already drilled wells
holding mineral interests. Each party could have its
on the property, but it approximates total gross acre-
own lease record delineating its interest in the lease,
age by operator.
which results in duplicate lease records, sometimes
numbering one hundred or more for the same mineral
tract. Eliminating duplicate records to determine acre1 A grantee is the entity receiving the lease of mineral rights.
After de-duplicating records and assigning leases,
where possible, based on well ownership, the result
is an interactive map with a single polygon for each
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leased tract, and an approximation of a company’s
dimensional view, there are only 200 leased acres, as
gross acreage. The Leasing Analytics module enables
shown in Figure 2. The markers note the original lease
users to analyze active versus expiring leases, quick-
acres and the primary term of the lease.
ly view lease details for all grantees, and identify high
quality acreage using Analytics proprietary graded
acreage model.
Methodology
The Analytics team outlines the area shared by leases
and creates unique polygons for each shape, as well
as the residual acres. The three 100-acre leases become four distinct polygons and each one is assigned
the earliest instrument date and longest expiration
In order to perform spatial modeling, the Analytics
date. Thus, Figure 3 shows four, fifty-acre polygons,
team relies on work performed by over 30 Drillinginfo
each with different dates.
geographic information system (GIS) technicians who
map individual lease polygons based on the legal description of the lease. Leasing data coverage varies by
state, but is approximately January 2002 through present2, and the lease polygons include direct links to the
lease details stored in Drillinginfo databases. The Analytics team employs a multi-step process to account for
duplicate lease records and to assign leases to operators based on well ownership.
The new unique shapes retain their original lease history and shape, but when they are added together, they
represent a single gross acreage count by grantee.
This approach results in a single count of acreage for
a lease at the grantee level, with links to all the grantor
lease records that pertain to the acreage.
Note: A mineral tract may still show up under multiple
grantees on the map, but this is often because of timing
Remove Duplicate Lease Records
It is very common for multiple lease records to be filed
for each mineral tract, sometimes with more than 100
records per tract. The duplicate lease records are removed using a spatial approach.
The Analytics team analyzes the boundaries of reported lease polygons and identifies duplicate records in a
simulated vertical stack. Figure 1 shows three leases
that are each 100 acres and have the same grantee. A
summation would indicate 300 leased acres, however
they overlap each other so if they are laid flat in a two
2 For details of leasing coverage by state, please see our website: http://info.drillinginfo.com/coverage/.
differences. For example, Operator A may have taken a
lease for three years, let it expire, and then Operator B
leased it. Both records show up in the leasing module
unless the user filters to narrow the time period.
Assign Effective and Expiration Dates and Activity
Status
Since we have records of the underlying lease documents pertaining to a single polygon, the Analytics
team can identify the effective instrument date and
relevant expiration date associated with the lease.
The lease documents for each unique grantee may
have varying instrument expiration dates, so the Analytics team identifies the earliest effective date, and
2
50
50
50
2007–2010 Acres (AC)
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50
B: 100 AC
2010–2013
C C: 100 AC
2013–2016
B
50
A
50
50
Acres (AC)
50
the latest expiration date from among the records and
assigns those dates to the lease.
We also track activity status and expiration status for a
lease, based on the following business rules:
Active status: “Yes” to the Active flag indicates that the
Figure 1. Three leases
lease had a permit filed, or production reported on it,
within the last 12 months. A lease is also considered
Active where a producing wellbore,3 or a wellbore
A: 100 AC
2007–2010
1
50 AC
2007–2010
permitted in the past 12 months, touches any portion
of the tract, even if there is no production associated
2
50 AC
3
B: 100 AC
2007–2013
50 AC
2010–2016
C
B2010–2013
A
it. Because the Analytics projects focus on unconven4
50 AC
2013–2016
C: 100 AC
2013–2016
tional formations, there may be additional production
or wellbore trajectories in conventional formations that
impact the Active status. We do not account for these
possibilities and they may require further due diligence
by the end user.
Expiring Status: The “Expiring Flag” in Leasing Ana-
50
50
50
Acres (AC)
50
lytics indicates whether or not a lease is expected to
become available upon its expiration date. “Yes” indicates the lease will potentially expire at the end of
Figure 2. Leases in two-dimensional view
its term because neither permits nor production have
1
50 AC
2007–2010
been reported for the lease in the last twelve months.
2
50 AC
2007–2013
“No” indicates the lease has already expired.
3
50 AC
2010–2016
C
B
A
4
50 AC
2013–2016
The leasing map defaults to show all leases from 1999
to current. If a lease expired and was not flagged as
Active, it still shows up on the map unless the date
range is filtered to after the lease’s expiration date.
The combination of Expiring and Active flags allows users to sort leases based on if, and when, they may be3 Wellbores are drawn based on directional surveys. We only
include surveys associated with wells that fall within the Analytics
project date and reservoir filters.
Figure 3. Gross leased acres
1
50 AC
2007–2010
3
2
50 AC
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EXPIRING YES
ACTIVE YES
ACTIVE NO
EXPIRING NO
N/A; active leases will not be shown as expiring
Lease is past term (already expired) but there is
activity so it is held
No permits filed or production reported in last 12
Already expired but no reported activity; may be
months; no wellbores crossing land; lease expected to available land
expire at end of term if no new activity
Table 1
come available. Table 1 above summarizes the possi-
If the 80% ownership requirement is not met, then a
ble combinations and their associated interpretations.
spatial assignment is not applicable.6 For example, if
two operators have each drilled 50% of the wells on a
Assign Grantee Leasehold to Operators Where
lease, there is no 80% owner and no assignment would
Possible
be made. To determine possible ownership, hover on
After de-duplicating the lease records, the resulting
leases are assigned to operators. A grantee on the
the wellbore trajectories to see a pop-up box describing which operator owns the wells.
lease record may not be the operator, such as situations when a broker takes a lease on behalf of an operator. Leases may also change ownership during acquisitions/divestitures.
The Analytics team uses production records to establish ownership within a county. If 80% or more of the
wells on a grantee’s total leasehold within a county
are owned by a specific operator, the grantee’s leasehold is assigned to the operator. Exhibit 2 includes a
visual representation of this type of spatial assignment.4 The green polygons in Figure 1 are leases listing
Double H Land Service as grantee. However, since at
least 80% of the wells on the land are owned by EOG,
the leases are assigned to EOG, as shown in Figure 2.5
4 A spatial analysis defines data by a location in space, or by a
shape, and then evaluates how these shapes relate to each other.
5 Based on discussions with landmen, the Analytics team
assumed that a lease brokerage company would not be leasing for
two operators in the same county at the same time as this could
present a conflict of interest.
6 Sometimes the operator reporting production has a different
name in our database than the grantee, even though they are
the same company. For example, EOG Resources is the grantee
for EOG leases, but spatial assignment analysis may assign the
lease to EOG, the reported operator. Therefore the leasing module
shows acreage for both EOG and EOG Resources.
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Conclusion
The Analytics leasing module is an exploratory tool to
better understand leasing activity over time in a specific play. By using spatial mapping algorithms, we deduplicate records to determine a unique acreage count
by grantee for a lease. In addition, spatial modeling allows us to approximate gross acreage for an operator
based on well ownership.
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delivers innovative oil & gas solutions that enable
our customers to sustain a competitive advantage
in any environment.
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the rest because they are able to be more efficient
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Copyright © 2015, Drillinginfo, Inc.
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WP_DI Analytics Leasing_06; 11/04/15
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Exhibit 1: Lease Tracts by Grantee
Green polygons represent leases with Double H Land Service as the grantee, and yellow polygons represent leases
with EOG Resources as the grantee. At least 80% of the wells on Double H Land leases are EOG wells.
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Exhibit 2: Lease Tracts by Assignment
Double H Land Service leases have been spatially assigned to EOG.
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