Petrophysics
PetrophysicsTo survive in this industry we need to continuously add value to all of our projects. Petrophysics can help meet this objective by;
- Recognising undervalued assets and investment opportunities,
- Avoiding over-valued investment opportunities,
- Reducing project development costs,
- Identifying project risk factors.
In this report we describe several projects where Henderson Petrophysics was able to use practical petrophysics to increase project value or to reduce the chance of capital loss.
Case Studies - Adding Project Value with Petrophysics
Increasing Booked Hydrocarbon Reserves in Thinly Bedded Reservoirs
Research by Don Henderson at the Exxon Production Research Company demonstrated that conventional formation evaluation techniques in thinly bedded reservoirs always results in a dramatic underestimate of in-place hydrocarbon volumes. The research project showed that under estimation of reserves results from the combination of the limited vertical resolution of logging tools and the use of "net" cut-off parameters. In the worst-case scenario, thin sands in a low net to gross section can appear to have no recoverable hydrocarbons.
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Case Study 1: Laminated Turbidite Reservoirs - Taranaki Basin, New Zealand
Small fields in this basin contain oil in laminated turbidite reservoirs. Resistivity is very subdued in the producing reservoir sections. Conventional log analysis methods make the reservoirs appear to be very shaly with low hydrocarbon saturation. The use of traditional cutoff values for porosity, shale content and Sw indicates that the deposit contains only minimal net oil sand.
Don Henderson used his extensive knowledge of log response in thinly bedded formations combined with outcrop studies and core data to develop an innovative petrophysical model that used conventional logs to determine sand thickness, porosity and hydrocarbon saturation. The model results were consistent with core data and provided data for realistic reserves estimates.
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Case Study 2: Nearshore Marine Sands - Krishna-Godavari Basin, Offshore India
Prior to the start of development drilling on this field Don Henderson undertook an review of available petrophysical data. This study showed that the previous operator had used traditional formation evaluation techniques that had dramatically underestimated in-place reserves by about. This serious under valuation of the hydrocarbon resource resulted from failure to recognize the effects of thin beds on log response and also the importance of understanding the distribution of shale in the reservoir.
Extensive coring of early development wells in this field showed that the reservoir consists of thinly bedded to laminated and bioturbated clean sands with high porosity and exceptional permeability. Don Henderson developed an innovative log analysis model that incorporated the results of the core study. The resulting log analysis estimates of net sand, porosity and hydrocarbon saturation were in very good agreement with core data. The petrophysical model and supporting core data confirmed that the previous operator had significantly underestimated field reserves.
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Case Study 3: Laminated Gas Reservoir, Offshore Bangladesh:
Laminated gas sands in this field were deposited in a very high energy deltaic environment. The highly productive gas sands have very subdued formation resistivity. Conventional log analysis techniques indicate that the reservoirs have a low net-to-gross ratio, are very shaly, and have high water saturation.
Early in the field development phase a Joint Venture partner had used a conventional log analysis methodology that resulted in a very pessimistic assessment of reservoir quality and field reserves.
Cores cut through some of the reservoirs allowed Don Henderson to recognize that the low formation resistivity was due to lamination of sand and shale. It was also obvious, from the core data, that it would be impossible to determine the porosity and gas saturation of individual sand laminations. Don quickly developed a petrophysical model to determine cumulative sand thickness (depth-integration of sand fraction), average sand porosity and hydrocarbon pore volume thickness (depth-integration of hydrocarbon pore volume). Core analysis and production test data confirmed the optimistic analysis results indicated by the Henderson analysis.
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Case Study 4: Heavy oil in thinly bedded sand-shale formation, Yemen
Don Henderson was asked to provide an opinion on the expected size of the oil resource in a large structure in Yemen. Management urgently required this information for a Joint Venture meeting scheduled to discuss possible development of the oil field.
Available log (FMS) and core data showed that the oil occurs in very thinly bedded to laminated sands. As expected, the very subdued formation resistivity resulted in extremely pessimistic conventional log analysis results that were not in agreement with either the well test data or with the production history from similar fields in the basin.
There was not enough time available to develop a comprehensive petrophysical model to evaluate the field. Instead, Don Henderson used FMS images, core descriptions, core analysis results (routine and SCAL) and conventional log data to determine sand thickness, porosity and hydrocarbon saturation.
RFT formation pressure data was used to establish the field oil-water contact. Although the pressure data was excellent, the water and oil pressure gradient lines were so close that it was very difficult to visually determine the free water level. Don developed an EXCEL spreadsheet to statistically determine the free water level (OWC). This spreadsheet is available in our Free Downloads section.
Using a depth-structure map at the top of the reservoir (conformable with reservoirs) and RFT pressure data Don then calculated in-place oil reserves. At the subsequent Joint Venture meeting, this reserves estimate was accepted by the participants in favor of the estimate submitted by the Operator.
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Adding Value by Recognizing Changing Formation Water Salinity
The following two case studies demonstrate how a very experienced formation evaluation specialist can add value by recognizing anomalous log analysis results and then finding an appropriate solution to difficult formation evaluation problems. Case Study 5 discusses a field where a hydrocarbon zone is underlain by very fresh water aquifers. Case Study 6 discusses a farm-out proposal where the vendor of a development prospect used inappropriate log analysis parameter selection that contributed to a huge overestimation of in-place reserves.
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Case Study 5 - Increase in hydrocarbon saturation (and reserves) - Snapper Field, Gippsland Basin, Australia
This field consists of a very thick gas zone with a thin (9m) oil leg. Reservoirs are massive fluvial sands with very high porosity and exceptionally high permeability. Sands below the hydrocarbon column contain very low salinity formation water (about 1700 ppm NaCl equiv.).
The traditional method of using water zone salinity to evaluate hydrocarbon saturation resulted in an apparently long transition zone and indicated that the oil zone would either produce water or oil with an uneconomic water cut.
During logging of the first field development well Don Henderson recognized that water salinity in the hydrocarbon zone was probably much higher than in the water zone. When capillary pressure data became available Don demonstrated that his initial analysis was correct and that the hydrocarbon zone water salinity was close to 30,000 ppm which is similar to other producing fields in the basin. Capillary pressure data also showed that there was unlikely to be a significant transition zone in this field.
Booked reserves in the oil zone are about 60 percent higher than indicated using the tradition of relying on parameters in the water zone. Oil production from the thin oil leg has far exceeded expectations and has further confirmed the results of the careful petrophysical analysis. Value has been added to this project by the early recognition of anomalous water salinity values.
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Case Study 6 - Decrease in hydrocarbon saturation (and reserves) - Gas Field in South-East Asia
This is an example where the operator grossly overestimated gas reserves. Value is added by recognizing that the property is over valued.
Mud log gas shows were indicated over a long interval of this interbedded sand and shale formation. Porosity and permeability are very low and decrease through the interval of interest. No significant hydrocarbons were produced during well testing. The operator attributed this lack of formation productivity to the effects of formation damage.
Examination of available data by Don Henderson indicated that the operator had used an arbitrary water salinity change (increase) at the top of the reservoir to increase apparent gas saturation (and reserves). Close examination of log and core data clearly showed that there was no justification for the water salinity value used by the operator.
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Adding Value by Discovery of Additional or Bypassed Hydrocarbon Reservoirs
Case Study 7: Tuna Field, Gippsland Basin, Australia
Gas and oil In this Intra-Latrobe formation field occur in fluvial sands interbedded with shale and coal. The field has a very complicated fluid system with many internal oil-gas and oil-water contacts.
Don Henderson who was very familiar with the field geology was the logging witness for the final field development well that was drilled in a crestal location. This well intersected oil in the lowest logged sand even though this sand was below the field oil-water contact. Don immediately arranged for the well to be deepened. The deepened section of the well discovered 2 additional oil pools.
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Case Study 8: Producing Field, Taranaki Basin New Zealand
In this project Don Henderson was asked to examine logs to report on reservoir quality in this mature producing field. Although log quality was poor, Don identified an oil sand near the bottom of the well that had not previously been recognized. This discovery led to a new exploration play and a field development project in this structurally complex area.
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Value Added by Recognizing the Potential for Loss of Capital
Good petrophysics can identify situations where a hydrocarbon resource has been pessimistically evaluated. It can also identify situations where a gross overestimation of in-place hydrocarbons almost guarantees that investment capital would be lost.
Case Study 9 describes how an operator overestimated both in-place gas reserves and the potential of the field to produce gas at commercial rates.
Case Study 10 describes how a gas exploration prospect was over valued because the operator did not closely examine available petrophysical data.
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Case Study 9: Gas Field - South East Asia
This is the same field described in Case Study 6 where the operator used a water salinity value that resulted in an overestimation of in-place gas reserves.
The operator incorrectly calibrated log analysis porosity estimates with ambient core porosity data. Correction for the effects of reservoir confining pressure showed that the operator's porosity estimate was significantly too high. In this low porosity reservoir small errors in porosity estimation result in very large changes to calculated gas saturation. The combined effect was that the operator estimate of in-place gas reserves was far too high.
The operator attributed the lack of significant well test gas flows to the effects of formation damage. However, this conclusion was based on both the overly optimistic gas saturation and the use of ambient permeability values. When corrected for the effects of reservoir confining pressure the average permeability is only about 5 to 10 percent of the ambient (surface condition) permeability values.
After examination of the available data Don Henderson reported to his management that the field was unlikely to contain significant producible gas reserves and was unsuitable as an investment.
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Case Study 10: Gas Exploration Project - Onshore, USA
Don Henderson was asked supervise TD logging and to provide wellsite log interpretation for this onshore gas exploration well. Prior to the logging job Don examined core, logs and petrographic data from the only well in the basin to have penetrated the target reservoirs. This examination quickly showed that the operator had not adequately understood the available data and consequently had probably grossly over-estimated the economic potential of this project.
Target reservoirs in this gas prospect are shaly sands with little or no visible porosity . Some of the sands contain carbonaceous material and occasional coal laminae.
A basin petrographic analysis indicates that the sands are highly lithic and have a volcanic provenance. Feldspars have been largely altered to carbonate and authigenic clay with associated microporosity.
Core analysis of the "best sands" from the early well indicated that porosity ranges up to about 11 percent. Measured permeability was zero to 1 millidarcy. Core measurements were made at ambient confining pressure.
From the limited log suite available the original operator had calculated porosity from the sonic log using a matrix transit time of 52.5 microseconds per foot. Calculated porosity ranged up to 21.5 percent with an average of 13 percent. For the exploration prospect economic analysis the vendor used this porosity value and an average hydrocarbon saturation of 65 percent.
A review of the data suggested that the matrix transit time used to calculate porosity was probably too low and resulted in over-estimation of porosity by about 1 percent. Core examination, experience with log response in this type of geological environment and knowledge of typical porosity probability distributions indicated to Don that the higher calculated porosity values resulted from the effect of coaly material on the sonic log. A more realistic "central tendency" value for porosity was calculated to be about 10 percent. This value agrees with the available core data. Petrographic data shows that some of this porosity is non-effective microporosity associated with altered feldspars.
Don used his experience with capillary pressure data to show that expected average hydrocarbon saturation was far lower than 65 percent and that the hydrocarbon charge was likely to be only about 30 percent of the value used by the vendor to "sell" the prospect.
The lesson here is that the financial backers of this project were not adequately informed of the petrophysical risks of this project.
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Value Adding by Reducing Field Development Costs
The two case studies below describe how value was added to a petroleum development project by limiting capital expenditure on formation evaluation. An additional objectives in both case was the requirement that data was adequate to describe the reservoirs.
Although the objective was to reduce overall costs both case studies show the critical importance of having core data.
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Case Study 11: Taranaki Basin, New Zealand
This field contains oil reserves in several very small pools. Since individual oil pools are small, the field economics are very sensitive to capital expenditure. Drilling costs in this rich agricultural area are very high and rather inflexible. An effort was made to reduce formation evaluation costs to improve project viability.
The oil reservoirs are laminated to very thinly bedded turbidite sands. Core and outcrop data showed that sands have very little clay matrix and that porosity is almost constant.
The logging contractor recommended high resolution log acquisition and processing in an effort to resolve the properties of individual sand beds. The cost of this was a 50% surcharge on the survey costs. However, cores and outcrop analogues showed that individual sands were far thinner than the vertical resolution of conventional logging tools so that these tools could not possibly fully resolve the properties of individual reservoirs. Trial logging runs in an early development well showed that by lowering the logging speed of the nuclear tools (Gamma Ray, Neutron, Density) and by not applying filters it was possible to obtain logs with resolution and repeatability equal to the high resolution processed logs. The only cost was a very slight increase in rig costs for the additional time taken to slow the logging tools through the target reservoirs.
Don Henderson developed a log analysis model that used conventional log data and that incorporated the results of the core and outcrop studies. Shale fraction from the neutron-density logs was converted to an equivalent clean sand thickness. This value was depth-integrated over the reservoir to determine net sand thickness. Average sand porosity was obtained by removing the total porosity contribution from the shale fraction. Depth integrated hydrocarbon-pore-volume was used to determine average oil saturation.
The lesson in this example is that cost effective but innovative log data acquisition procedures and interpretation methods can be used to evaluate complex reservoir using conventional log data.
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Case Study 12: Directive to reduce capital expenditure - Oil and gas field, Offshore Krishna-Godavari Basin, India
As a condition for obtaining permission to develop this field, government authorities set a limit on field development capital expenditure.
One way to reduce field development costs was to limit expenditure on formation evaluation. Wireline logging was put out to competitive bid. One of the bid replies contained a proposed "high technology" option to help evaluate this complicated reservoir. This option was twice as expensive as that for a conventional logging suite. An additional cost for the "high technology" option was rig time required to run the additional logging tools.
Detailed core examination showed that the reservoir sands were very clean and that shale occurred as laminations, clasts and as framework grains. Also, log data showed that shale parameters were very constant through the reservoir section. Don Henderson used these observations to develop a log analysis model that used conventional logs to determine sand thickness, porosity and hydrocarbon saturation. The results from this model matched very well with core data.
The data obtained from the conventional logs proved to be completely adequate for reservoir description. An independent auditor certified the hydrocarbon reserves calculated using the evaluation model.
In addition to the cost savings, the conventional logs minimized rig time required for logging. This proved to be vital because of very difficult logging conditions in most of the deviated wells. In most of the wells the hole deteriorated extremely quickly and it would have been impossible to run the "high technology" logging tools.
The lesson in this example is that it is possible to save money and still obtain high-quality formation evaluation results with conventional data. Another lesson is that good core data is essential for development of innovative interpretation methods.
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