Pore Pressure and Methods of Analysis Section 4 PPFG Modeling Process Part 3 Selection of Shale Points

Part 3.???Selection of Impermeable Strata and Elimination of Permeable Formation Members

???????????????Of all the models I’ve reviewed enforcing QA and exercising QC, if there were inadequacies and/or weaknesses in the models, the most common was due to not sufficient time and effort applied to selection of impermeable shale points for input into the model. Selecting shale points is tedious and laborious. However, a rigorous examination of the logs and a thorough evaluation and selection of shale points has a dramatic effect on the precision and credibility of the pore pressure model.

After the overburden gradient is calculated, the modelling process can begin. Compaction pore pressure models utilize impermeable formation members, thus it is necessary to eliminate the permeable formation members from the data being used to calculate pore pressure. To accomplish this, only clays are selected for analysis, and sands and permeable limestones are eliminated from the pore pressure calculations.

All pore pressure models are impermeable formation models. There is not a verifiable model that determines the pressure of a permeable formation because the pressure of the fluid in a permeable formation is a function of the hydraulic head, and a change in fluid pressure has very little effect on resistivity, sonic travel time, interval velocity, or density. Thus, the information and data collected by oil exploration is not sufficient to directly predict the pressure of a permeable formation. Prediction of pressure in a permeable formation requires direct pressure measurement at an offset location, and/or assumptions of continuity and hydraulic head calculations using the centroid concept.

Geophysical models (resistivity, sonic, interval velocity) are compaction models that detect changes in the porosity trend and associate that porosity trend change with a change of pore pressure.

Shale intervals are selected for analysis in the resistivity and sonic models. The seismic velocity will combine sands and shale. Sometimes the analyst may be able to discriminate between thick shale formation members and sandy members with seismic surveys. However, most commonly the resolution of seismic is not sufficient to allow this with a significant degree of certainty.

For a single depositional sequence there will be a recurring shale deposit that can be identified on the logs and used for analysis. On the surface of the area of deposition, there are various energy levels determining the grain size distribution of sediments deposited. As burial progresses, a specific grain size distribution will migrate around regions within the area of deposition. A specific grain size distribution will move away from a specific location, then after an amount of burial return to the location. After multiple episodes of a similar grain size distribution returning to the same location, in a vertical sequence penetrated by a well bore there will be a recurring clay that can be chosen for use in the pore pressure model.

It is beyond the point of diminishing returns to expend the time and effort to attempt to identify the exact same grain size distribution in clay throughout a depositional sequence. This is to be taken into consideration by the analyst, and their selection of shale points included in their model must take this characteristic of sedimentation into consideration. The more similar the shale points selected, the more precise the model will be.

For a specific normal compaction trend, the shale intervals selected must be similar in geochemistry for the resistivity model, and physical characteristics for the sonic and interval velocity models.

???????????????Most commonly, only the Gamma Ray log is considered for selection of clay deposits to include in the pore pressure model. All available logs should be used to select shale intervals. Potassium-rich sources result in high Gamma Ray for shales, and lower Gamma Ray for silica and carbonate sands. However, there are occurrences of feldspar sands with a high Gamma Ray value. All available logs should be used to verify shale picks.

Increased silt in shale will cause a slight reduction of Gamma Ray, often undetectable, considering the characteristics of data collection of Gamma Ray tools. When the silt content becomes significant, micro permeability develops and introduces water into the model causing the resistivity to decrease unrelated to pore pressure, as well as the Δt to increase unrelated to pore pressure. Use of resistivity and sonic tolls help identify these zones so they can be eliminated from the model.

Increased carbonate in shale will cause a reduction of Gamma Ray, and like increased silt content, it is not precisely detected by the Gamma Ray tool. This increase in carbonate will cause an increase in resistivity unrelated to pore pressure, and cause the model to calculate lower pore pressure when the actual pore pressure gradient did not change, or an increase in pore pressure gradient was not calculated when the pore pressure gradient increased.

Cemented and lithified zones cause the resistivity to increase and the Δt to decrease unrelated to pore pressure. Cementation and lithification will have the same effect the above change in carbonate content had on the calculated pore pressure gradient being less than actual.

For the purpose of simplicity and brevity necessary for the allowable duration of this class, we will demonstrate clay selection characteristics using the Gamma Ray log. It is the responsibility of the analyst to understand how to use multiple logs to determine lithology, and to use that knowledge.

Figure 31.???????????Example Shale Picks by Maximum Gamma Ray Peaks and Pore Pressure Calculations

???????????????Shale points are selected by establishing a shale baseline in the Gamma Ray track. For every Gamma Ray value greater than the value of the Shale Baseline, the corresponding data points in the resistivity data set are selected and included in the model for calculation of pore pressure.

???????????????For this example, only the peaks of the Gamma Ray log are chosen. The black dots in the resistivity track are the resistivity data points corresponding to the Gamma Ray values greater than the Shale Baseline. A Normal Compaction Trend Line (NCTL) is established associated with the selected resistivity data points in accordance with the definition of normal compaction trend. The shallowest section is assumed to be hydrostatically pressured, and the NCTL was drawn to approximate that portion of the data set.

???????????????At approximately 5,900 feet the pore pressure calculation indicates a slight rise above hydrostatic pressure, then returning to hydrostatic at 6,300 feet where it begins to rise again, returning to hydrostatic at 6,700 feet. Given the geology is a continuous clastic depositional sequence with no effective pressure seals, this is highly unlikely. The determination of what depth the pore pressure rises above hydrostatic cannot be determined with any significant degree of confidence. Also, the line drawn to connect the resulting calculations appear to be very angular, and an increased degree of precision is desired. To accomplish this, we increase the number of resistivity data points selected by moving the Shale Baseline to the left (lower value of Gamma Ray), selecting a wider range of clay characteristic.

Figure 32.???????????Example Number of Shale Picks Increased by Moving Shale Baseline to Increase Number of Resistivity Data Points

???????????????Shifting the Shale Baseline to the left increased the number of corresponding resistivity data points selected for input into the pore pressure model. In the above example, broad strokes of the Shale Baseline are used to select shale points. Using broad strokes produced a relatively irregular line when the pore pressure gradient calculations for each resistivity data point selected are connected with a line. Again, there are two depths where the pore pressure calculation indicates the pressure rises above hydrostatic, at 6,500 feet and 6,700 feet.

???????????????To achieve a more representative resistivity data set of shale picks, shale points can be individually selected using small segments of the Shale Baseline. In significantly thick depositional sequences with relatively high rates of deposition, this is not frequently necessary. However, in older rocks of thinner depositional sequences, often this is the only method of acquiring a representative resistivity data set of shale points.

Figure 33.???????????Selecting Shale Points individually Using Small Segments of the Shale Baseline

???????????????Individually selecting the shale points had a significant effect on the smoothing of the calculated pore pressure gradient line. However, there are still two possible depths where the pore pressure possibly rises above hydrostatic, at approximately 6,300 and 6,600 feet.

A universally accepted scientific method of analyzing data within a representative data set is the use of a moving average. Applying a moving average to the resistivity data points selected generates a representative value with depth of the shale selected for input into the pore pressure model.

Figure 34.???????????Applying a Moving Average to Resistivity Data Points Selected

???????????????Applying a moving average allows the determination that the pore pressure rises above hydrostatic at approximately 6,350 feet, and increases its rate of increase at approximately 6,750 feet. Such precision of the model significantly increases the confidence and validity of the pore pressure model.