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The Hunt for Acquisition and Drilling Prospect Leads*

By

Mike Cherry¹

Search and Discovery Article #40122 (2004)

*Adapted from oral presentation, entitled “Using Industry Applications Software for Analyzing Data to High Grade Acquisition and Drilling Prospects,” at AAPG Mid-Continent Section Meeting, Tulsa, OK, October 12-14, 2003, and at Tulsa Geological Society Meeting, March 9, 2004.

¹CEC Energy Consultants, The Woodlands, Texas (www.CECEnergyconsultants.com) ([email protected])

Abstract

Recent years have seen remarkable technological advances in industry applications software that is capable of analyzing large corporate and/or industry databases, giving geoscientists and engineers the capability of high grading and screening acquisition and drilling prospects.

Using industry applications software, geoscientists and engineers can sort through large datasets to categorize/compile information in order quickly to make generalizations and gain knowledge and background information on a play or trend. This presentation will provide many methods for analyzing data in order to high grade acquisitions, identify field development opportunities, identify areas within a basin that have significant multiple pay zone potential, set up regional or basin-type databases for quick look determinations for auction or acquisition screening and evaluations, and to focus on hot areas of activity.

This presentation will also demonstrate methods of how to use industry software applications and industry data to identify areas of permeability and bypassed productive pay zones that either a geoscientist or engineer could use quickly to sort data and generate acquisition and drilling prospect leads.

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

uAbstract

uIndustry software

uFigures 1-6

uMapping software

uAcquisition prospects

uDrilling prospects

uFigure 7

uUnder-utilized functions

uFigures 8-14

uUnder-utilized analyses

uFigures 15-23

uFigures 24-30

uDarcy equations & PI

uFigures 31-38

Available Industry Software

Figure Captions (1-6)

	Figure 1. Cross section prepared using Landmark – Geographix software.
	Figure 2. Illustration showing components for use of Geoplus – Petra software.
	Figure 3. Map with lines of cross sections, showing example of mapping using Schlumberger – GeoQuest software.
	Figure 4. Software for analysis of reserves and economics. A. IHS – Power Tools. B. Landmark – Aries. C. OGRE Partners – OGRE. D. Schlumberger – Merak Peep.
	Figure 5. Production curve, for a well in the Watonga-Chickasha Trend, Anadarko basin, Oklahoma, used for estimate of reserves.
	Figure 6. Data in Microsoft Access are readily exported, as desired. A. PEC0701PDP: database. B. Top Value PV10>407,200.

Return to top.

Mapping Software Tools (Figures 1, 2, and 3)

· Landmark – GeoGraphix (Figure 1)

· Geoplus – Petra (Figure 2)

· Schlumberger – GeoQuest (Figure 3)

Reserves and Economic Software (Figure 4)

· IHS – Power Tools

· OGRE Partners –OGRE

· Landmark – Aries

· Schlumberger – Merak Peep

Automated EUR Reserve Estimates (Figure 5)

Access Database Exports (Figure 6)

Common Uses of Mapping Software

· Mapping attribute, net pay, isopach, and structure

· Cross sections—stratigraphic and structural

· Gridding and contouring techniques

· Management presentations

· Acreage position management

· Field development management

· Mainly used by drafting and geo-tech personnel

Common Acquisition Prospect Identification

· Contact A&D brokers to see what they represent that is for sale.

· Auctions

· Make contacts of larger companies that typically sell large volumes of properties and attempt a negotiated purchase.

Common Development Drilling Prospect Identification

(Figure 7)

· Analyze existing HBP acreage position for infill or extensional opportunities.

· Analyze offset operators to HBP acreage position for anomalies or drainage problems.

· Identify field extension opportunities.

· Analyze existing non-producing acreage position for drilling potential..

Figure Caption (7)

Figure 7. Structure map, base of Lower Cretaceous Ferry Lake, Driscoll field, East Texas, showing pie diagrams to illustrate well-by-well production (oil as green; gas as red).

Under-Utilized Analytical Functions

(Figures 8, 9, 10, 11, 12, 13, and 14)

· Petrophysical and detailed log analysis

· Volumetric reserve analysis of reservoirs

· Identify/compare performance and success

· Determine continuity and compartmentalization of reservoirs.

Figure Captions (8-14)

	Figure 8. Structure map and isopach of Cretaceous D sand, Denver basin field. Map by Paul H. Jones.
	Figure 9. Cross plot of density porosity and neutron porosity.
	Figure 10. Log correlation of section containing Cretaceous D sand, Denver basin.
	Figure 11. Structure map, on I sand, West Basian Bay area, Plaquemines Parish, Louisiana.
	Figure 12. Chromatogram, providing fingerprint of a hydrocarbon.
	Figure 13. Compartmentization by virtue of faulting, separating wells in the northeast from those to the southwest.
	Figure 14. Additional fault segment (to those shown in Figure 13), for providing required compartmentization of well 3.

Petrophysical and Detailed Log analysis (Figure 9)

· Log calculations – porosity, S_w, K, lithology

· Identify O/W or G/W contacts.

· Calculate volumetric reserves.

Volumetric Reserve Analysis (Figure 11)

· Calculate volumetric reserves by producing interval of a field, basin, or region.

· Compare theoretical with actual reserves.

· Identify anomalies for rework, recompletion, or redrill opportunities.

Analyzing Performance and Success of Other Operators

· Identify most successful operators by year comparing EUR’s and dry holes with drilling/completion dates.

· Map areas of regions successful operators are active.

· Compare their activity and success with your regional interpretation.

Continuity and Compartmentalization (Figures 12, 13, and 14)

· Verify/confirm continuity or compartmentalization of a reservoir.

· Identify gas chromatograph fingerprints of oil or gas sample from producing zone(s).

· Compare fingerprints of zones of offset wells to identify extensional or development opportunities.

Under-Utilized Acquisition and Drilling-Prospect Analysis

· Perform kh equivalent and EUR analysis.

· Perform DST analysis for permeability indicators.

· Perform Darcy’s calculation for well productive analysis.

· Identify high PI well anomalies

Figure Captions (15-23)

	Figure 15. Density-neutron porosity plot, showing net pay and estimate of 2,770,000 barrels of oil in-place/40 acres.
	Figure 16. Database used in computing cumulative and average production rate: First 24 months of production of well, with unique well ID 35-045-21435-0000 (ERSALLUNIT).
	Figure 17. Data statistics, for first 24 months of production for well with unique well ID 3504-045-21435-0000 (ERSALLUNIT).
	Figure 18. Transform equation for calculation of Pseudo kh: Pseudo kh = (First 24 months production) / 1532341.
	Figure 19. Database with production data for well with unique well ID 3504-045-21435-0000 (ERSALLUNIT)
	Figure 20. Image of screen for creating contour grid for the first 24 months of production.
	Figure 21. Image of screen for creating contour grid for EUR (ultimate gas reserves)
	Figure 22. Map of cumulative gas production for first 24 months of production, in part of Anadarko basin, Oklahoma.
	Figure 23. Map of cumulative gas production for first 24 months of production (same as Figure 22), showing wells with production ratio of 0.50 to 14.00.

Pseudo kh Analysis (Figures 15, 16, 17, 18, 19, 20, 21, 22, and 23)

· Calculate first two years of production.

· Determine minimum and maximum with statistical analysis.

· Normalize the data.

· Map it just like you would with kh data.

· Compare it with EUR’s with overlays.

DST Analysis as Permeability Indicators (Figures 24, 25, 26, 27, 28, 29, and 30)

· Use to analyze regions or basins for prospect leads.

· Compare areas of high permeability with EUR’s for anomalies.

· Identify areas of high permeability and low EUR’s as indicative of damaged zones.

Figure Captions (24-30)

	Figure 24. Diagrammatic sketch of DST and resulting data.
	Figure 25. Results of DST, from well in 3-11-60-3W5, Alberta basin, Canada.
	Figure 26. Log suite, including density porosity, of pay section.
	Figure 27. Database of test data, showing variables to extract.
	Figure 28. Database of test data, with transform equation, Pseudo k = (FFP/FSIP).
	Figure 29. Map of cumulative gas production for first 24 months of production (same general area as Figure 22), with relatively high-k areas highlighted.
	Figure 30. Diagram illustrating the technique for determining pressures during DST.

Basics of DST Testing (Figures 24 and 25)

· ISIP=FSIP, reservoir not depleted or limited

· IHP=FHP and >SIP’s, no significant mud loss and a good test for using data

· Large fluid recoveries = good permeability

Calculating k from DST’s (Figures 26, 27, 28, 29, and 30)

· Calculate ratio of FFP/FSIP.

· Higher ratio is indicative of good k.

· FP/SIP ratios with fluid recoveries – 75% higher than without fluid recovery, indicating higher k.

· High FP/SIP with little or no fluid recovery is indicative of near wellbore damage.

Permeability Indicators

· High k, where FP is closer to SIP

· Low k, where FP is much smaller than SIP

· FSIP<ISIP is indicative of depletion or limited reservoirs.

Darcy Equations and Productivity Analysis

(Figures 31, 32, 33, 34, 35, 36, 37, and 38)

· Calculate which wells should be capable of producing if no damage exists.

· Compare theoretical flow rates with actual flow rates for anomalies.

· Identify wells that can be reworked or redrilled.

Figure Captions (31-38)

	Figure 31. Database of production data, with transform equation: Est Flow = (7.08)KH(P1-P2)/((B)(V)(7)).
	Figure 32. Database of production data, with transform equation: Flow difference = (Est Flow – Act Flow).
	Figure 33. Map of well control, of same area as Figure 22 , showing wells with difference in initial production rates.
	Figure 34. Database of well data, with transform equation: Pseudo PI = (Cum/(P1-P2))
	Figure 35. Map of cumulative production for first 24 months of production, along with wells with high pseudo kh (in same area as Figure 29 ). Click to view sequence of maps shown in Figures 22, 23, 29, 33, and 35-respectively, 24-months production, wells with production ratios of 0.50-14.00, areas of relatively high k, wells with difference in initial production rates, and wells with high pseudo kh.
	Figure 36. Map showing most positive curvature (trend analysis) in terms of reservoir attributes, western Anadarko basin, Oklahoma, utilizing 17,718 wells.
	Figure 37. Map of most positive curvature (trend analysis) in terms of reservoir attributes, western Anadarko basin, Oklahoma (same as shown in Figure 36), with representative key wells highlighted (of 3321 wells).
	Figure 38. Structure form map, western Anadarko basin, Oklahoma (as overlay to most positive curvature--Figure 37), with representative key wells highlighted (of 3321 wells).