Laboratory Measurements Of Porosity Research Articles

Field observations of soil hydrological flow path evolution over 10 millennia

Abstract. Preferential flow strongly controls water flow and transport in soils. It is ubiquitous but difficult to characterize and predict. This study addresses the occurrence and the evolution of preferential flow during the evolution of landscapes and here specifically during the evolution of hillslopes. We targeted a chronosequence of glacial moraines in the Swiss Alps to investigate how water flow paths evolve along with the soil-forming processes. Dye tracer irrigation experiments with a Brilliant Blue FCF solution (4 g L−1) were conducted on four moraines of different ages (30, 160, 3000, and 10 000 years). At each moraine, three dye tracer experiments were conducted on plots of 1.5 m ×1.0 m. The three plots at each moraine were characterized by different vegetation complexities (low, medium, and high). Each plot was further divided into three equal subplots for the application of three different irrigation amounts (20, 40, and 60 mm) with an average irrigation intensity of 20 mm h−1. The day after the experiment five vertical soil sections were excavated, and the stained flow paths were photographed. Digital image analysis was used to derive average infiltration depths and flow path characteristics such as the volume and surface density of the dye patterns. Based on the volume density, the observed dye patterns were assigned to specific flow type categories. The results show a significant change in the type of preferential flow paths along the chronosequence. The flow types change from a rather homogeneous matrix flow in coarse material with high conductivities and a sparse vegetation cover at the youngest moraine to a heterogeneous infiltration pattern at the medium-age moraines. Heterogeneous matrix and finger flow are dominant at these intermediate age classes. At the oldest moraine only macropore flow via root channels was observed in deeper parts of the soil, in combination with a very high water storage capacity of the organic top layer and low hydraulic conductivity of the deeper soil. In general, we found an increase in water storage with increasing age of the moraines, based on our observations of the reduction in infiltration depth as well as laboratory measurements of porosity. Preferential flow is, however, not only caused by macropores, but especially for the medium-age moraine, it seems to be mainly initiated by soil surface characteristics (vegetation patches and microtopography).

Petrofacies classification using machine learning algorithms

Carbonate reservoirs represent a large portion of the world’s oil and gas reserves, exhibiting specific characteristics that pose complex challenges to the reservoirs’ characterization, production, and management. Therefore, the evaluation of the relationships between the key parameters, such as porosity, permeability, water saturation, and pore size distribution, is a complex task considering only well-log data, due to the geologic heterogeneity. Hence, the petrophysical parameters are the key to assess the original composition and postsedimentological aspects of the carbonate reservoirs. The concept of reservoir petrofacies was proposed as a tool for the characterization and prediction of the reservoir quality as it combines primary textural analysis with laboratory measurements of porosity, permeability, capillary pressure, photomicrograph descriptions, and other techniques, which contributes to understanding the postdiagenetic events. We have adopted a workflow to petrofacies classification of a carbonate reservoir from the Campos Basin in southeastern Brazil, using the following machine learning methods: decision tree, random forest, gradient boosting, K-nearest neighbors, and naïve Bayes. The data set comprised 1477 wireline data from two wells (A3 and A10) that had petrofacies classes already assigned based on core descriptions. It was divided into two subsets, one for training and one for testing the capability of the trained models to assign petrofacies. The supervised-learning models have used labeled training data to learn the relationships between the input measurements and the petrofacies to be assigned. Additionally, we have developed a comparison of the models’ performance using the testing set according to accuracy, precision, recall, and F1-score evaluation metrics. Our approach has proved to be a valuable ally in petrofacies classification, especially for analyzing a well-logging database with no prior petrophysical information.

Evaluating petrophysical properties of volcano-sedimentary sequences: A case study in the Paraná-Etendeka Large Igneous Province

Abstract The Parana-Etendeka represents a major magmatic province associated with the rifting of West Gondwana and the formation of the South Atlantic Ocean. The area represents a direct analogue for similar aged volcanic rocks buried within hydrocarbon-rich basins offshore the South Atlantic margin. We present here a detailed integration of outcrop data with laboratory measurements of porosity, permeability, and ultrasonic acoustic velocities (P and S-waves) for volcanic and interbedded sedimentary rocks of the Parana-Etendeka Province in southern Brazil. The lava pile is formed of compound pahoehoe basaltic lavas at the base (Torres Formation) followed by thick tabular rubbly pahoehoe basaltic andesites (Vale do Sol Formation) and the upper stratigraphy is characterized by locally fed domes and extensive tabular acidic units. Sedimentary interbeds occur throughout the entire lava pile. For the volcanic rocks petrophysical properties have a cyclic variation controlled by the lava internal structure. Lava upper and lower crusts have relatively high porosity (>10%) and low acoustic velocities, whilst lava flow cores are characterized by porosities of less than 5% and velocities typically 0.5–1.0 kms−1 higher than lava crust facies. The highest porosities are found in the upper crust of both rubbly pahoehoe (c. 28.3%) and pahoehoe lavas (c. 26.6%) where vesicles account for most of the pore space. Permeability is relatively low in the volcanic rocks ( 15%) and permeability (avg. 450 mD) and represent the best reservoir rocks within the Parana-Etendeka Province. Nevertheless, where diagenesis is intense porosity and permeability are significantly diminished. The petrophysical properties of volcanic rocks are controlled primarily by lava emplacement mechanisms (e.g. inflation, degassing and flow fragmentation), and secondarily by bulk mineral composition. Petrophysical properties can be further modified by diagenetic and hydrothermal alteration processes. Understanding the interplay between primary and secondary processes on the final petrophysical characteristics of the rocks is key for defining reservoir properties in offshore areas, such as the North and South Atlantic margins, where volcanic rocks are intrinsically associated with prolific hydrocarbon-bearing sedimentary basins.

What is the role of tortuosity in the Kozeny-Carman equation?

Hydraulic tortuosity is an important parameter in characterizing fluid-flow heterogeneity in porous media. The most basic definition of tortuosity is the ratio of the average flow path length to the sample length. Although this definition seems straightforward, the lack of understanding and the lack of proper ways to measure tortuosity make it one of the most abused parameters in rock physics. Hydraulic tortuosity is often treated merely as a fitting factor, or worse, it is neglected by being combined with a geometric factor in the Kozeny-Carman (KC) equation. Often, the tortuosity is obtained from laboratory measurements of porosity, permeability, and specific surface area by inverting the KC equation. This approach has a major pitfall because it treats tortuosity as a fitting factor, and the inverted tortuosity is often unphysically high. In contrast, we obtained the tortuosity from 3D segmented binary images of porous media using streamlines extracted from a local flux, the output from the lattice Boltzmann method (LBM) flow simulation. After obtaining streamlines from each sample, we calculated the distribution of tortuosities and flux-weighted average tortuosity. With the tortuosity measurement from streamlines, every parameter in the KC equation can be measured accurately from 3D segmented binary images. We found, however, that the KC equation is still missing some important geometric information needed to predict permeability. With known parameters and without a fitting factor, the KC equation predicts permeability higher by one to two orders of magnitude than that predicted by the LBM. We searched for a missing parameter by exploring various concepts such as connected pore space and pore throat distribution. We found that the connected pore space does not contribute to the difference between the KC permeability and LBM permeability, whereas, as we learn with sinusoidal pipe examples, the pore throat distribution captures what is missing from the KC equation.

Study cases of thermal conductivity prediction from P-wave velocity and porosity

Laboratory measurements of porosity, P-wave velocity and thermal conductivity from samples from two geothermal reservoirs in France and Australia are compared to the predictions from different models involving mineralogical considerations, and effective medium theory models yields <10% error in dry and saturated conditions in the Australian aquifer, and <30% deviation under saturated conditions in the French reservoir. Thermal conductivity derived from models involving detailed mineralogy is in good agreement with laboratory-measured data. Possible explanations for minor discrepancies using SEM/XRD include the effects of secondary minerals (i.e. ±undetected carbonates and fine particles) and the hydration of clays.

Characterization of the porosity distribution in the upper part of the karst Biscayne aquifer using common offset ground penetrating radar, Everglades National Park, Florida

• We use common offset GPR to rapidly characterize porosity in karst limestone. • We demonstrate the ability of GPR to characterize subsurface heterogeneities. • The CRIM petrophysical model is used to build field scale GPR-based porosity models. The karst Biscayne aquifer is characterized by a heterogeneous spatial arrangement of porosity and hydraulic conductivity, making conceptualization difficult. The Biscayne aquifer is the primary source of drinking water for millions of people in south Florida; thus, information concerning the distribution of karst features that concentrate the groundwater flow and affect contaminant transport is critical. The principal purpose of the study was to investigate the ability of two-dimensional ground penetrating radar (GPR) to rapidly characterize porosity variability in the karst Biscayne aquifer in south Florida. An 800-m-long GPR transect of a previously investigated area at the Long Pine Key Nature Trail in Everglades National Park, collected in fast acquisition common offset mode, shows hundreds of diffraction hyperbolae. The distribution of diffraction hyperbolae was used to estimate electromagnetic (EM) wave velocity at each diffraction location and to assess both horizontal and vertical changes in velocity within the transect. A petrophysical model (complex refractive index model or CRIM) was used to estimate total bulk porosity. A set of common midpoint surveys at selected locations distributed along the common-offset transect also were collected for comparison with the common offsets and were used to constrain one-dimensional (1-D) distributions of porosity with depth. Porosity values for the saturated Miami Limestone ranged between 25% and 41% for common offset GPR surveys, and between 23% and 39% for common midpoint GPR surveys. Laboratory measurements of porosity in five whole-core samples from the saturated part of the aquifer in the study area ranged between 7.1% and 41.8%. GPR estimates of porosity were found to be valid only under saturated conditions; other limitations are related to the vertical resolution of the GPR signal and the volume of the material considered by the measurement methodology. Overall, good correspondence between GPR estimates and the direct porosity values from the whole-core samples confirms the ability of GPR common offset surveys to provide rapid characterization of porosity variability in the Biscayne aquifer. The common offset survey method has several advantages: (1) improved time efficiency in comparison to other GPR acquisition modes such as common midpoints; and (2) enhanced lateral continuity of porosity estimates, particularly when compared to porosity measurements on 1-D samples such as rock cores. The results also support the presence of areas of low EM wave velocity or high porosity under saturated conditions, causing velocity pull-down areas and apparent sag features in the reflection record. This study shows that GPR can be a useful tool for improving understanding of the petrophysical properties of highly heterogeneous systems such as karst aquifers, and thus may assist with the development of more accurate groundwater flow models, such as those used for restoration efforts in the Everglades.

Laboratory measurements of porosity, permeability, resistivity, and velocity on Fontainebleau sandstones

The relations among the resistivity, elastic-wave velocity, porosity, and permeability in Fontainebleau sandstone samples from the Ile de France region, around Paris, France were experimentally revisited. These samples followed a permeability-porosity relation given by Kozeny-Carman’s equation. For the resistivity measurements, the samples were partially saturated with brine. Archie’s equation was used to estimate resistivity at 100% water saturation, assuming a saturation exponent, [Formula: see text]. Using self-consistent (SC) approximations modeling with grain aspect ratio 1, and pore aspect ratio between 0.02 and 0.10, the experimental data fall into this theoretical range. The SC curve with the pore aspect ratio 0.05 appears to be close to the values measured in the entire porosity range. The elastic-wave velocity was mea-sured on these dry samples for confining pressure between 0 and [Formula: see text]. A loading and unloading cycle was used and did not produce any significant hysteresis in the velocity-pressure behavior. For the velocity data, using the SC model with a grain aspect ratio 1 and pore aspect ratios 0.2, 0.1, and 0.05 fit the data at [Formula: see text]; pore aspect ratios ranging between 0.1, 0.05, and 0.02 were a better fit for the data at [Formula: see text]. Both velocity and resistivity in clean sandstones can be modeled using the SC approximation. In addition, a linear fit was found between the P-wave velocity and the decimal logarithm of the normalized resistivity, with deviations that correlate with differences in permeability. Combining the stiff sand model and Archie for cementation exponents between 1.6 and 2.1, resistivity was modeled as a function of P-wave velocity for these clean sandstones.

Regional trends in matrix porosity and dry density of the Chalk of England

Abstract Laboratory measurements of porosity and dry density are presented for 2045 core samples from the Chalk of England. The data are subdivided on the basis of gross stratigraphy, i.e. Lower, Middle and Upper Chalk, and into four geographical areas: Northern England, East Anglia, Thames &amp; Chilterns and Southern England. Statistical analysis of the data shows (i) that the porosity distributions for the Upper Chalk of the Southern and Thames &amp; Chilterns regions are indistinguishable, (ii0 that the porosity distributions for the middle and Lower Chalk of the East Anglian region are indistinguishable, and (iii) that the porosity distributions for each of the gross stratigraphical units from all other regions are statistically discrete. Porosities range from 3.3% to 55.5%, with a mean porosity of 34.0%. Dry densities range from 1210 kg/m 3 to 2510 kg/m 3 , with a mean dry density of 1790 kg/m 3 . In a given region there is a trend of increasing porosity from Lower to Middle to Upper Chalk. There are systematic variations in porosity between the regions. There is a trend of increasing porosity from the Northern England region to the Southern England region, to the Thames &amp; Chilterns region, to East Anglia. No significant systematic variations in porosity-depth gradients were observed. Chalk porosity-depth gradients are typically high, of the order of -0.07 to -0.1 porosity per cent per metre.

Compressional velocity and porosity in sand‐clay mixtures

Laboratory measurements of porosity and compressional velocity were conducted on unconsolidated brine saturated clean Ottawa sand, pure kaolinite, and their mixtures at various confining pressures. A peak in P velocity versus clay content in unconsolidated sand‐clay mixtures at 40 percent clay by weight was found. The peak in velocity is 20–30 percent higher than for either pure clay or clean sand. A minimum in porosity versus clay content at 20–40 percent clay by weight is also observed. Such behavior is explained using a micro‐geometrical model for mixtures of sand and clay in which two classes of sediments are considered: (1) sands and shaley sands, in which clay is dispersed in the pore space of load bearing sand and thus reduces porosity and increases the elastic moduli of the pore‐filling material and (2) shales and sandy shales, in which sand grains are dispersed in a clay matrix. For these sediments, the model reproduces the extrema in velocity and porosity and accounts for much of the scatter in the velocity‐porosity relationship.