Building the Wireline Database and Calculation of Reservoir Porosity

Transcription

1 This presentation is a publication of the Bureau of Economic Geology at The University of Texas at Austin. Although it is posted here as a source of public information, those wishing to use information contained in this document are respectfully requested to reference the author(s) appropriately. Please cite this document as follows: Kane, Jeffrey, 2004, Building the wireline database and calculation of reservoir porosity: The University of Texas at Austin, Jackson School of Geosciences, Bureau of Economic Geology, If you wish to use figures or text contained in this document, or wish to obtain further information regarding its contents, please contact the author.

2 Building the Wireline Database and Calculation of Reservoir Porosity Jeff Kane Bureau of Economic Geology ExxonMobil Fullerton presentation, November 16 th and 17 th, 2004

3 Outline Overview wireline log/core database Porosity log normalization process Calibration to core porosity Conclusions

4 Overview of log database Fullerton Clear Fork contains log suites that span the entire history of logging in the U.S. The earliest logs are the electric logs of the 1940 s. The most recent logs include the standard logs run today along with many of the high technology tools presently available.

5 Overview of log database Early in the life of the project, after initial review of the then current ExxonMobil database, ExxonMobil made the decision to redigitize all the logs from the entire field. This effort lasted almost two years, and resulted in 1206 wells being digitized by ExxonMobil.

6 Overview of log database 324 wells with log data were received from Oxy-Permian to include in the study. 57 of these wells had data useful across the Clear Fork. These wells were combined with the ExxonMobil dataset resulting in the final database (1263 wells with data across the Clear Fork).

7 All 1263 wells containing log data across the Clear Fork

8 Overview of log database The redigitized data received from ExxonMobil, was received simultaneously with the characterization project. This resulted in multiple database rebuilds. The final database rebuild, in December of 2003, resulted in a database of 18,000 log curves.

9 Overview of log database All wells had basic quality control work done. Log curves were verified and a comparison of the digital curve and the paper copy were made. Detailed quality control was performed on ~300 wells initially and then randomly throughout the remainder of the project.

10 Overview of log database Also during this time 74 wells with core data were transcribed into a digital format, yielding in excess of 30,000 entries. Of these 30 proved to be of direct use in the characterization project and were loaded in with the logs (~14,500 entries).

11 Overview of log database The log suites in Fullerton field can be divided into four sections chronologically. These will be discussed in historical order from earliest to most recent.

12 Overview of log database The first group, as previously mentioned, were the electric logs of the 1940 s. This log suite was comprised of a spontaneous potential, a long lateral, a short normal, and a limestone lateral. These logs were not used for evaluation except in some special cases to try an estimate original water saturation.

13 Example of an electric log suite from FCU 2150 Spontaneous Potential -160 MV 40 DEPTH FEET Short Normal 0 OHMM 100 Limestone Lateral Lateral 0 OHMM OHMM

14 Overview of Log Database The second group, common in the 1950 s, incorporated a gamma-ray neutron log into the electric log suite. These tools vary considerably in design, measurement type and overall quality. Because of the wellbore environment of many of these logs, use of these logs in analysis turned out to untenable at this time.

15 Example of a gamma-ray neutron from FCU 1432 Gamma ray 0 GAPI 125 DEPTH FEET 7000 Neutron 450 NAPI Scale Change Lower Clear Fork 7100 Wichita CASING

16 Overview of Log Database The third group, common from the mid s s through the mid s s contained a Sidewall Neutron Log and a deep resistivity (Dual Laterolog or Dual Induction). First group to contain a calibrated porosity log. First group that contained data to be used quantitatively in the characterization.

17 320 wells total in this group 316 wells were actually used (displayed)

18 Example of an SNP-DLL log suite from FCU 1437 Gamma ray 0 GAPI 150 Caliper 6 IN 16 DEPTH FEET 7050 Sidewall Neutron Porosity Deep Laterolog 0.2 OHMM 2000 Shallow Laterolog 0.3 V/V OHMM 2000 Lower Clear Fork Wichita

19 Overview of log database The most recent group started about the mid s s and continues through today. It is dominated by Compensated Neutron Logs, most often run by themselves and run in cased hole.

20 Overview of log database A subset of this group contains more complete log suites, including density, sonic, resistivity logs. Less commonly more advanced tools such as photo-electric factor logs, formation testers, electromagnetic propagation logs, image logs and digital sonic logs are also available.

21 471 wells total in this group 437 were actually used (displayed)

22 Example compensated neutron log from FCU 1845 Gamma ray 0 GAPI 150 DEPTH FEET 7100 Compensated neutron porosity 0.3 V/V

23 733 wells used for computing porosity Combines SNP and CNL wells Some overlap 20 wells contain both logs

24 Porosity log normalization Compensated neutron logs and sidewall neutron logs were normalized separately. Separate normalization is necessary because the matrix tool response in each case is quite different.

25 Porosity log normalization The assumption was made for normalization is the average and the standard deviation of porosity across a stratigraphic interval varies gradually, if at all, across the field.

26 Normalization example DEPTH FEET Gamma Ray Compensated neutron porosity 0 GAPI V/V Lower Clear Fork Wichita 7050

27 Normalization example DEPTH FEET Gamma Ray Compensated neutron porosity 0 GAPI V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

28 Normalization example DEPTH FEET Gamma Ray Layer averaged compensated neutron porosity 0.3 V/V -0.1 Compensated neutron porosity 0 GAPI V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

29 Normalization example For every well in the normalization group, an average and standard deviation of the layer averages are computed. This is a vertical averaging process designed to reduce local rock variation, i.e. random error.

30 Normalization example These values are mapped and a moving average the values are computed at each well location. This is a lateral averaging process to correct logs that have problems like calibration errors, i.e. systematic error.

31 Normalization example This moving average acts as a low-pass filter enhancing longer order field wide trends. These estimated averages and standard deviations from the moving average (lateral averaging) are taken to be the correct values at each well location and the log is transformed to reflect these new values.

32 Normalization example DEPTH FEET Gamma Ray 0 GAPI 150 Layer averaged compensated neutron porosity Compensated neutron porosity 0.3 V/V -0.1 Normalized compensated neutron porosity 0.3 V/V V/V -0.1 Compensated neutron porosity 0.3 V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

33 Calibration to core After normalization the log response still does not reflect actual porosity values. Two calibrations were done for each porosity log type (CNL, SNP), one for dolomite and one for limestone. These two calibrations were done differently due to the distribution differences between dolomite and limestone in the field.

34 Calibration example DEPTH FEET Gamma ray Core porosity 0 GAPI V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

35 Calibration example DEPTH FEET Gamma ray Layer averaged core porosity 0.3 V/V -0.1 Core porosity 0 GAPI V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

36 Calibration example DEPTH FEET Gamma ray 0 GAPI 150 Layer averaged core porosity Core porosity 0.3 V/V -0.1 Layer averaged core porosity 0.3 V/V V/V -0.1 Layer averaged neutron porosity 0.3 V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

37 Calibration example Dolomite calibration line for compensated neutron Uses layer averaged porosities Equation for line is phit = x NPHI norm Colors vary by well Layer averaged core porosity (V/V) Layer averaged normalized CNL porosity (V/V) 0.300

38 Calibration example Limestones are thin enough with respect to the cycle thickness that their effect gets averaged out. Point by point calibration using a PEF cutoff (PEF > 4) PEF dolomite = 3 PEF limestone = 5 PEF limestone Gamma ray 0 GAPI 150 L2105 L2100 flowlayer_w2 flowlayer_w3 Lower Clear Fork Wichita DEPTH FEET Photo-electric factor 0 B/E 10 Normalized neutron log 0.3 V/V -0.1

39 Calibration example Limestone calibration line for compensated neutron Uses actual log/core porosities Equation for line is phit = x NPHI norm Colors vary by well Core porosity (V/V) Normalized CNL porosity (V/V)

40 Calibration example DEPTH FEET Gamma ray 0 GAPI 150 Layer averaged core porosity 0.3 V/V -0.1 Core porosity 0.3 V/V -0.1 Layer averaged core porosity 0.3 V/V -0.1 Layer averaged neutron porosity 0.3 V/V -0.1 Core porosity 0.3 V/V -0.1 Total porosity from log 0.3 V/V -0.1 L L2100 Lower Clear Fork Wichita flowlayer_w2 flowlayer_w3 7050

41 Conclusions Fullerton Field has four major log suites that can be defined chronologically. Only those logs that were run in the 1960 s and later were used in the quantitative porosity computation. This is about 60% of the wells in the total database. Quality control and auditing were a major effort in this project resulting in a high quality database delivered to ExxonMobil

42 Conclusions A moving average window in porosity log normalization can enhance field wide trends and minimize systematic errors such as calibration errors in log data. Averaging data by cycles helps reduce local variability, helps to minimize the effects of differing vertical resolutions and reduces the effects of minor lithologic variations.