determining petrophysical and hydrogeological parameters ... · olga filiptsova* sheryl ryan dwer...

AEGC 2019: From Data to Discovery – Perth, Australia 1

Determining petrophysical and hydrogeological parameters from historical bore logs for the Leederville-Parmelia aquifer, northern Perth Basin, using regression methods Olga Filiptsova* Sheryl Ryan DWER DWER 8 Davidson Terrace, Joondalup 8 Davidson Terrace, Joondalup [email protected] [email protected]

INTRODUCTION

Calculating the hydraulic properties of an aquifer is an essential step in any hydrogeological assessment or groundwater model. Current methods for determining hydraulic characteristics include the laboratory testing of core material, field testing of aquifers, analysis of geochemical tracers, groundwater modelling and analysis of borehole geophysical logs. These are generally costly and time intensive processes that also incorporate levels of uncertainty. For example, hydraulic parameters obtained from aquifer testing are averaged across the entire screened interval. This can be problematic where hydraulic conductivity and storage

vary significantly across a profile due to vertical heterogeneity (Senior and Goode, 1999). In 2017, the Department of Water and Environmental Regulation (DWER) began the East Midlands groundwater investigation as part of the State Groundwater Investigation Program (SGIP). The investigation area is located on the Dandaragan Plateau 170 km north of Perth in the Perth Basin, between the towns of Moora (north) and Gingin (south). The investigation is primarily focussed on the regionally important Leederville-Parmelia aquifer. The aquifer is under considerable pressure from climate change and localised abstraction, with the demand for groundwater in the area continuing to grow. The objectives of this investigation are to gain an understanding of the geological and hydrogeological characteristics of the multi layered Leederville-Parmelia aquifer, including understanding of connectivity with the overlying Surficial and Mirrabooka aquifers and identifying where the aquifers are separated by confinement from the Kardinya Shale Member of the Osborne Formation. The investigation aims to build a 3D conceptual hydrostratigraphic model of this complex multi layered system to enable DWER to deliver evidence-based groundwater management decisions. Between 2017 and 2019, 17 new monitoring bores over 9 locations were established in the Leederville-Parmelia aquifer. A comprehensive suite of borehole geophysical logs were run on the deep bore at each location, covering natural gamma, spectral gamma (T232, K40, U238), resistivity, temperature, caliper and borehole magnetic resonance (BMR). Borehole geophysical logging is a well-known technology that is broadly used in hydrogeological investigations. Recently, borehole magnetic resonance (BMR) has gained popularity in the groundwater industry. BMR can be used to provide major hydrogeological parameters such as the volume of free fluid (effective porosity or specific yield), the volume of clay and capillary bound water (specific retention), permeability (hydraulic conductivity) and pore size distribution. A workflow was developed in an attempt to see if this new data could be used to gain additional information from historical bores in the area. This workflow uses a linear regression analysis to correlate data between the current and historical investigation bores. Using this workflow the main mineralogical and geological factors affecting aquifer properties were determined. Critical hydrogeological parameters such as specific yield and hydraulic conductivity as well as salinity profiles were calculated for the entire hydrostratigraphic column. Calculated parameters were determined for historical bores with only

SUMMARY A new workflow of bore data re-interpretation that increases the value of old data with only a minimal cost has been developed. The workflow estimates hydraulic and petrophysical parameters from historical bore data, providing clay volume, total porosity, effective porosity or free fluid, permeability, hydraulic conductivity and salinity profiling. Hydraulic parameters were calculated for bores installed in the Leederville-Parmelia aquifer in the northern Perth Basin during 2018 and 2019 by using natural gamma ray, resistivity and borehole magnetic resonance logs. The bores were sampled and the laboratory analysis of water salinity was used to verify the accuracy of the computations. Using a regression analysis to correlate the “old with the new”, estimates for these parameters were then calculated for older bores that only had natural gamma logs, resistivity logs and geological logging details available. The calculated salinity values from the historical bores were validated using existing chemistry sampling. This workflow facilitates the calculation of hydraulic parameters across a regional area and potentially reduces the timing and resourcing of investigation programs by increasing the information available from historical bore data. Key words: borehole magnetic resonance (BMR), aquifer, linear regression analysis, uncertainty analysis, historical bore data, clay volume, total porosity, effective porosity or free fluid, permeability, hydraulic conductivity and salinity profiling.

Regression methods for determining petrophysical and hydrogeological parameters Filiptsova and Ryan


limited available downhole geophysical data sets adding value to the regional groundwater investigation. Estimated parameters were validated with results from complementary geophysical datasets and chemistry laboratory analyses. The workflow was developed and evaluated using Paradigm® petrophysical software Geolog®.

METHODOLOGY

Figure 1 shows the workflow which consists of three input paths of data: the natural gamma log, the resistivity log and the BMR log. In the East Midlands area, clay volume or clay/sand ratio is the major factor impacting aquifer parameters. This is supported by the BMR data which has a high correlation coefficient of 0.75-0.92 between clay volume and the volume of free fluid as shown in Table 1. The clay volume (VSH) in a bore can be calculated from a natural gamma log by using a standard linear method:

𝑉𝑆𝐻 =GAMMA− GAMMA)*+,-.

(GAMMA01*23 − GAMMA)*+,-.) (1)

where GAMMA is the measured natural gamma, GAMMA01*23 is the gamma value of an interval consisting of 100% shale and GAMMA)*+,-. is an interval that is predominantly sand. The values used for GAMMA01*23 are driven by clay type. For the East Midlands area the gamma values for clay and sand vary across formations, for example the Kardinya Shale Member of the Osborne Formation has a much lower gamma value than the clay gamma values in the Leederville Formation or Parmelia Group sediments. For this reason, the intervals used to calculate VSH are based on stratigraphic units. A regression analysis on the BMR data showed that in the Leederville-Parmelia aquifer the maximum amount of free fluid in the formation is approximately 35% and when the clay volume is more than 80% there is no free fluid in the sediments (Figure 2).

Figure 2. An example of the crossplot VSH vs FFV for NGG17.

From this analysis the empirical formula for calculating the free fluid volume (FFV) was developed and is shown in Equation 2 𝐹𝐹𝑉 = 0.4 − 0.5 ∗ 𝑉𝑆𝐻 (2) Total porosity (TPOR) can be obtained from the BMR data. It is a sum of the volume of free fluid, capillary bound water (CAPWV) and clay bound water (CBWV): 𝑇𝑃𝑂𝑅 = 𝐹𝐹𝑉 + 𝐶𝐴𝑃𝑊𝑉 + 𝐶𝐵𝑊𝑉 (3) Using a frequency histogram analysis, the TPOR value from the BMR data shows the average percentage of volume by volume of capillary bound water in the sand interval is 0.12v/v and 0.25 v/v for clay bound water. Thus, Equation 3 can be modified in the following way: 𝑇𝑃𝑂𝑅 = 𝐹𝐹𝑉 + 𝑉𝑆𝐻 ∗ 0.25 + (1 − 𝑉𝑆𝐻) ∗ 0.12 (4) The VSH values from Equation 1 and the FFV values from Equation 2, can be put into Equation 4 to give the TPOR values. The Paradigm® petrophysical software Geolog® calculates Permeability (PERM) using the Coates Free Fluid Index method (Schlumberger Chart Perm-2, 2009) and is shown in Equation 5. 𝑃𝐸𝑅𝑀 = (70 ∗ 𝐹𝐹𝑉I ∗ (1 − 𝑆𝑤𝑖)/𝑆𝑤𝑖))I (5) where Swi is irreducible water saturation empirically estimated at 0.15 for the investigation area. Figure 3 (track 10) shows a comparison of the permeability values from the BMR data and the values generated in Geolog. The BMR data is processed using two different models – KSDR (from the Schlumberger Doll research model) and KTIM (from the Timur-Coates model). The hydraulic conductivity (K) in metres per day can then be calculated using Equation 6:

𝐾 =𝑃𝐸𝑅𝑀 ∗ r ∗ 𝑔

h (6)

where K – hydraulic conductivity (m/day), r - water density, 𝑔 – acceleration of gravity, h - dynamic viscosity. The resistivity log can be combined with the TPOR values to give the apparent formation water resistivity (RWA) using the Archie method for fully water saturated intervals: 𝑅𝑊𝐴 = (𝑅𝑡 ∗ 𝑇𝑃𝑂𝑅P)/𝑎 (7) where Rt is measured formation resistivity, m is cementing factor (constant value of 1.33) and a is the tortuosity for shaly sand which has a constant value of 1.65 (Carothers, 1968). A salinity profile for sand intervals can now be calculated using the RWA value from Equation 7 𝑅𝑊𝑁𝐴𝐶𝐿𝑝𝑝𝑚 = 10(V.WXIY2Z[(]^_Y`.`aIV))/`.bWW (8) where 𝑅𝑊𝑁𝐴𝐶𝐿 is the formation water salinity as the equivalent of NaCL in ppm (Backer Atlas, 2002).



RESULTS

The workflow was developed and validated using a suite of geophysical logs, primarily natural gamma, resistivity and BMR. Table 1 shows a high correlation between measured and calculated values for free fluid volume and permeability. Calculated salinity values were assessed against results from chemistry sampling and found to be accurate. Figure 3 is an example showing the calculated parameters against values obtained from the various geophysical logs. The calculated VSH is consistent with the natural gamma logs and the calculated FFV is consistent with the FFV from the BMR data. Calculated salinity values are consistent with chemistry sampling results in the screened interval. However, there is variation within the permeability values and it is possible that the Coates Free Fluid Index method slightly overestimates permeability in silted intervals. Table 1. Correlations between measured and calculated parameters.

The workflow was applied to a number of historical bores in the East Midlands area that had natural gamma and resistivity logs. Clay volume, free fluid, total porosity and salinity were calculated using the above equations. Figure 4 shows the results from two of these bores. Track 1 is the depth track, the Strata shown in track 2, track 3 presents the natural gamma, track 4 – deep resistivity and calculated water resistivity, track 5 is calculated clay volume, track 6 presents calculated free fluid and total porosity, track 7 is calculated permeability and track 8 shows calculated salinity profile and lab measured water salinity within the screen interval. The clay volume is consistent with high peaks in the gamma log. The calculated salinity values in the screened interval are consistent with results from chemistry samples.

DISCUSSION

The workflow was developed using new data from the Leederville-Parmelia aquifer in the East Midlands investigation area. The workflow has been applied to a number of historical bores in the area to calculate hydraulic parameters across a regional extent. A number of limitations have been encountered in the development of the workflow. From the results in Figures 2 and 3, the volume of free fluid appears to be overestimated in silted intervals. Due to the very small pore size in silted intervals, the fluid is capillary bounded. While this does not make any significant difference to the gamma values it can impact free fluid volume calculations in the BMR log. Geological bore log descriptions can be used to adjust the free fluid volume calculation.

Borehole drilling conditions can be a major limitation as wash outs can extend past the radius of influence for geophysical probes. In the East Midlands project, several logs produced near unusable data where there were significant wash outs. The presence of metal debris in one bore rendered the BMR data unusable. Several resistivity logs were unusable due to the high level of salt in the drilling muds. Steel surface casing was often required to go deeper than 50 m, resulting in a loss of data in the shallow sediments. Understanding the major factors effecting aquifer properties in an area is key to this workflow. In the East Midlands area, clay volume has the highest impact on hydraulic parameters in the Leederville-Parmelia aquifer. To identify gamma value end points for a geological unit, the clay type must be known. For this investigation, the mineralogy of several clay samples from each formation will be analysed using x-ray diffusion. The precision of the geophysical tools being used should be taken into account. The porosity precision of BMR tool is ±2 pu and the accuracy of gamma measurements is ±5%.

CONCLUSION

The workflow developed as part of the East Midlands groundwater investigation can be used to assign hydrogeological parameters to historical bore data, increasing its value significantly. It has the potential to increase the quality and quantity of data available for regional investigations while only incurring a minimal cost. The workflow is still in a preliminary stage and requires further validation including a thorough analysis of the limitations before it can be standardised for use in regional groundwater investigations. As the equations rely on regression methodology, the workflow is specific to an area. Linear regression analysis and the development of correlation coefficients would be required for new areas of investigation. The workflow can be applied over user defined intervals, leading to a better understanding of aquifer properties both laterally and vertically. This is beneficial to both conceptual and numerical groundwater models.

REFERENCES

Archie, G. E. The Electrical Resistivity Log as an Aid in Determining some Reservoir Characteristics, Transactions AIME, vol. 146,pp. 54-62, 1942. Backer Atlas, 2002, Introduction to Wireline Log Analysis, 48. Carothers, J. E., 1968, A statistical study of the formation factor relation: Log Analyst, September-October, 13-20 Schlumberger, 2009, Log Interpretation Charts, Perm-2, 270. Senior, L.A., and Goode, D.J., 1999, Ground-Water System, Estimation of Aquifer Hydraulic Properties, and Effects of Pumping on Ground-Water Flow in Triassic Sedimentary Rocks in and near Lansdale, Pennsylvania, U.S. Environmental Protection Agency.



Figure 1. The workflow for petrophysicsl/hydrogeological parameters calculations. Where FFV – volume of free fluid, PERM – permeability, VSH – clay volume, Sirr – irreducible water saturation, TPOR – total porosity, RW – formation water resistivity, RT – measured formation resistivity, RWNACL – formation water salinity in ppm.

Figure 3. Comparing measured and calculated parameters for bore NGG23A.



Moora Line 1 Moora Line 2

Figure 4. Example interpretation of the historical bores Moora Line 1 and Moora Line 2.

determining petrophysical and hydrogeological parameters ... · olga filiptsova* sheryl ryan dwer...

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