Regional Soil Resistivity For Corrosion Risk Assessment In The Niger .
Journal of Mining and Geology Vol. 57(2) 2021. pp. 271 - 281 0022-2763 Regional Soil Resistivity for Corrosion Risk Assessment in the Niger Delta, Nigeria Abam, T.K.S.1, Iduma, R.E.O.2, Udota, B.S.3 and Obasi, C.F.3 1 Institute of Geosciences and Space Technology, Rivers State University, Nkpolu, Port-Harcourt, Nigeria. 2 Department of Surveying and Geoinformatics, Akanu Ibiam Federal Polytechnic, Unwana, Nigeria. 3 Groundscan Services Nig. Ltd, Lydia Abam Lane, Trans-Amadi, Port-Harcourt, Nigeria Corresponding E-mail: abam.kingdom@ust.edu.ng Abstract Oil Spills from Pipeline failures have resulted in widespread and costly environmental degradation. The reduction in pipeline thickness and ultimate failure are generally ascribed to corrosion from soils of high aggressivity, which are prevalent in the Niger delta. This paper presents aggregated data from 529 Vertical Electrical Soundings (VES) using a maximum current electrode separation of 30m, to generate a regional resistivity distribution to aid prediction of soil aggressivity and corrosion potential within the depths of pipeline engineering interest (1-10m). The apparent resistivity values were acquired using ABEM SAS 1000 with a mix of Schlumbeger and Wenner electrode configurations. The apparent resistivity values averaged over depths of 3m and 10m were plotted against the coordinates using Surfer-16 and overlaid on Google earth Pro to produce a spatial distribution with enhanced location visibility. The results show that corrosivity generally increases from the Coastal plain sand in the north of the delta to the Mangrove swamps in the coastal areas. The most severe corrosive sub-environments are at low elevations in poorly drained soils in the Mangrove swamps. The variation in the spatial distribution of the subsurface resistivity is attributed to a combination of influencing factors such as elevation above mean sea level, depth to water level, soil and groundwater quality, soil type and physical property. Results of this study provide guidance as to what ground resistivity to expect in different part of the delta as well as provide valuable information to assess the risks to assets either as a means of prioritizing maintenance or of improving design for new installations in the Niger Delta region. This paper therefore fulfills an identi? ed need to investigate the aggressivity and corrosivity of soils in the Niger Delta area with a view to providing adequate protection to underground transportation pipelines and other metallic assets in contact with or buried in the ground. Keywords: Resistivity, Corrosion, Aggressivity, Vertical Electric Sounding, Pipeline Niger Delta. Introduction either as a means of prioritizing maintenance or liability or of improving design for new installation. Besides, identification of potentially corrosive environments is precursor in deterioration modeling. Deterioration modeling of oil pipelines and water mains is an essential element to guide decision making in pipe rehabilitation or renewal programs. The Niger delta is one of the major oil and gas provinces in the world. It has an extensive and intricate network of pipelines built over the years to support production and transportation of hydrocarbon production the region. Due to corrosion, pipeline thicknesses have been reduced and in many cases breached, resulting ultimately to leakages that are reported as spillages. The high frequency of crude oil spillage incidences and the environmental consequences have become a source of great concern. According to Ukoba et al. ( 2011), a significant proportion of bursts and leaks are associated with corrosion of cast iron pipe systems laid without protection in the early sixties), but which in many places have failed to perform optimally that their replacement or repair is a matter of urgency. The close relationship between the soil environment in which most iron pipes are laid and the potential incidence of corrosion have been explored by several authors including Corcoran et al. (1977), Agunloye (1984), Khare and Nahar (1997), and Norhazilan et al. (2012), who have shown pitting corrosion in buried cast iron pipes has more to do with local soil properties rather than the material composition of the pipe. Guma et al. (2015), Mars (1987), Ekoh et al. (2012), Brand (2018), Simon et al. (2021) and Ekine and Emujakporue (2010) have shown that corrosion stems from material interaction with the environment and usually leads to material degradation process that jeopardizes safety and poses serious challenges in materials and engineering. While many other Writers have used geoelectrical investigation to evaluate soil corrossivity and aquifer protective capacity of overburden, some others have carried out similar studies to demonstrate that surface As a consequence therefore, to build new assets in potentially corrosive environment such as the Niger Delta and to manage old assets particularly utility pipelines, to prolong their life or to tackle repairs in a systematic way, there is an increasing need for detailed underground asset management information, particularly soil corrosivity. In this way, users will be able to use the information to assess the risks to assets 271
Journal of Mining and Geology Vol. 57(2) 2021. 272 direct measurements can be used to evaluate soil resistivity and monitor corrosion processes (Adeniji et al., 2014; Daryono et al., 2018; Obiora et al., 2015; Oki, Egai, & Akana, 2016; Okiongbo et al., 2019; Pritchard, Hallet, & Farewell, 2013; Thiesson, 2018). When a cast iron pipe is buried in the soil, the residual lifetime of the buried cast iron pipe begins to decrease under aggressive environmental conditions through corrosion. The Corrosion process involves an electrochemical reaction between the outer surface of an exposed pipe and its surrounding soil environment, facilitated by the potential difference between two points that are electrically connected in the presence of an electrolyte, in this case, the surrounding soil. Since corrosion is not a measureable parameter, it can only be evaluated indirectly through the assessment of soil corrossivity/aggressivity, which in itself is affected by several factors, the most critical being soil moisture content, acidity, aeration and electrical resistivity. Water is essential for the corrosion reaction to take place, and soils with a moisture content above 20% are thought to be particularly corrosive (Khare and Nahar, 1997). Soil acidity: The dissolution of metals is facilitated by acidic conditions. Consequently, the lower the pH, the higher the corrosion rate. Soil aeration on the other hand is considered to promote corrosion, especially if they contain soluble sulphates. Sulphate-reducing bacteria can grow in such soils if the pH value is in the range 5.5 – 9.0, although the most favorable conditions are near neutral (about pH 7.0). These bacteria reduce sulphates to sulphides, and the corresponding oxidation of elemental hydrogen is the reaction which involves them in corrosion mechanisms (Okiongbo et al., 2019). By far the most important factor, soil resistivity provides a measure of the concentration of soil electrolyte, which is essential in the corrosion process. Bradford (2000) regards the method of soil resistivity as being the most commonly used indicator of soil corrosivity. Burton (2001) found that resistivity correlated well with soil corrosivity classes. Soils with low resistivity will encourage corrosion, i.e. the lower the resistivity of the soil, the higher the corrosion rate. According to a study by Roberge (as cited in Safway, 2018), for most Table 1: A correlation of soil resistivity with soil corrosivity (Safeway, 2018) environments, the soil resistivity testing data provides an outstanding basis for assessing soil corrosivity. Table 1 shows a correlation of soil resistivity with soil corrosivity. The British Standards (BS-1377) formulated a classification system for soil aggressivity, here merged with corrosion specification by Escalante (1995) (Table 2). The overwhelming significance of resistivity was emphasized by Robinson (1993) when he described the relationship between environmental factors and the corrosive nature of soil, and reported that the soil resistivity has the most profound effect on soil corrosivity. In addition to being a valuable aid when interpreting the severity of corrosive areas, the determination of an appropriate ground bed location for optimum cathodic protection system, and the design of the cathodic protection are essentially based on shallow in-situ soil resistivity (Peabody, 1967). For this reason, electrical resistivity method are widely used in the investigation of soil aggressivity or corrosivity potential (Oki et al., 2016). Salem (1999) suggested that evidence concerning a subsurface soil type, its moisture content and aggressivity can be revealed from surface resistivity measurements. The soil electrical resistivity indicates the relative capability of the soil to carry electrical current. It is a main indicator of the corrosiveness of soils, as the rate of corrosiveness is a function of the electrical conductivity. Khare and Nahar (1997) reported that the electrical resistivity is highly significant in evaluating the strength Table 2: Classification of Soil Aggressivity/Corrosion Allowance by the British Standards (BS-1377)
Journal of Mining and Geology Vol. 57(2) 2021. of soil corrosivity and its classification, and that it is closely related to the soil properties, such as water content, salinity, soil texture etc, as the rate of corrosion is a function of the electrical conductivity. Ngah and Abam (2014) carried out shallow resistivity measurements for subsoil corrosivity evaluation in Port Harcourt metropolis in Southern Nigeria. Results from interpretation of electrical resistivity data from the area outlined two geoelectric layers which corresponds to an upper layer that is corrosive to moderately corrosive and a lower layer that is moderately to slightly corrosive, according to British Standard Soil Electrical Resistivity classi? cation. This classification is also in agreement with a correlation of soil resistivity with soil corrosivity by Safway (2018). They advised for proper protection of underground steel pipes for water distribution to prevent deterioration of water quality as a result of pipeline corrosion. 273 The water table in the region varies with season. Groundwater levels fluctuate in response to rainfall distribution in all but the mangrove swamp subenvironment. According to Abam (2016), the groundwater level, although season dependent, also vary across the Niger Delta region (Figure 2). The variation of the groundwater level which mimics the topography reveals the occurrence of groundwater mounds and receptacles within the regional groundwater flow system which promotes a resultant groundwater discharge to the Atlantic coastline. F The maximum depths to groundwater (7-10m) are recorded in the more elevated areas which comprise freshwater forest. This is followed by the floodplain areas which recorded 0-5m, the Beach ridges 0-1.5m and the mangrove swamp areas with depth to groundwater between 0-0.5m. Materials and Method Preliminary environmental impact assessment techniques are usually applied to prevent deterioration and failure of engineering structures. Some of the techniques may require knowledge of the subsurface distribution of resistivity in construction projects that would involve burial of steel pipes and cables, and other subsurface network of piping to prevent corrosion. Consequently, this paper explores the distribution of ground resistivity across the Niger Delta region. Geology and Geomorphology of the Study Area The Niger Delta is located in southern Nigeria between latitudes 4ºN and 6ºN, and longitude 3ºE and 6ºE (Figure 1). The area slopes gently from north to south. Average elevation stands at about 13-25m above sea level. The geology of the region is dominated by three lithostratigraphic units, Akata, Agbada and Benin Formations, overlain by various types of Quaternary deposits (Short and Stauble, 1967; Allen, 1965), all of which are of no direct engineering significance to corrosion. The Quaternary sediments overlying the Benin Formation consists of five geomorphic subenvironments, namely: the undulating lowland of the coastal plain sands, the flood plain of the lower Niger with extensive sand deposits, the meander belts consisting of wooded fresh water swamps, the salt water mangrove swamps and estuary complexes and the beach ridges. The network of pipelines described earlier, are usually embedded in these units, which comprise alluvial and hydromorphic soils and lacustrine sediments of Pleistocene age and which sediments thickness vary from 0-30m. In order to assess potential corrosion intensity and its spatial distribution within the Niger Delta region, 350 Vertical Electrical Soundings (VES) performed at different geo-referenced location in different seasons over the period (2003-2020) were collated and processed. VES, records the changes in resistivity with depth, and with the available geological information, correlation is done, to infer the depths and resistivity of the layers present (Vasantrao, 2017). Geophysical electrical soundings with four electrodes configuration, i.e., Wenner and Schlumberger methods, were carried out at the same selected sites, with maximum current electrode spacing of AB 30m. The ABEM Terameter, Model SAS 1000, which transmits a well defined and regulated square wave that minimizes induction effects and attenuation, was used for fieldwork to acquire all the data. Field precautions observed to ensure good VES data quality included firm grounding of the electrodes, and checking for current leakage and creeps to avoid spurious measurements. Whenever profiling was done parallel to an existing pipeline, reasonable offsets were observed away from the pipeline to avoid conductivity interference with the pipeline. The Schlumberger method (Figure 3), is based on measuring the potentials between a pair of electrodes, potential electrodes (M, N), while transmitting direct current (DC) between another electrode pair, current electrodes (A, B). In both methods of electric sounding, the depth of investigation is proportional to the separation between the current electrodes (A, B), and effective depth, z, of penetration by Wenner and
Journal of Mining and Geology Vol. 57(2) 2021. 274 Fig. 1: Distribution of Quaternary sediments in the Niger delta (Reijers, 2011) Fig. 2: Groundwater surface elevation along the traverse in the Eastern Niger delta Schlumberger arrays, is equal to AB/3 (VillalobosAragón, 2019; Vasantrao, 2017). By varying the electrical electrode separation, information about stratification of the ground is provided. difference (ÄVMN) and injected current, I, using (Sharma, 1997): The apparent soil resistivity (ñapp) for Schlumberger array is computed from the measurement of potential where .(1) .(2)
Journal of Mining and Geology Vol. 57(2) 2021. 275 denotes the "geometric factor" that will acquire a particular value for a given electrode configuration, ÄVMN represents the potential difference between the potential electrodes M and N, and I is the current injected into the ground. The geometric design for this array is shown in Figure 3. Two measurements were taken perpendicular to each other in two (x, y) directions at each test point. The, mean resistivity of the top layer (r o1m) and the mean resistivity of the subsoil (r o2m) were computed and used to determine the thickness (LTH) and average depth (LD) of the geological strata. In Wenner method (Figure 4), four electrodes of equal size, driven into the soil surface, are equally spaced along a straight line; the distance between adjacent electrodes, the array spacing, is equal to a constant value, a (Illias et al., 2021). A current, I is injected between the outer pair of the electrodes and the potential difference, ÄVMN is measured between the two inner pair of the electrodes. Wenner geometric factor (Sharma, 1997), assumes the simple form, K 2Ða. The equation of apparent resistivity valid for the mid-point between the potential electrodes (M, N), reduces to: Mean resistivity of top layer (r o1m) was obtained with the following relation (Burger, 1992) : .(5) where, n number of test points r o1 mean value of the two values measured along the two directions in the point I, given in (Ùm). Mean resistivity of subsoil layer (ro2m) was computed with the following relation : .(3) .(6) The knowledge of the seasonal variation of the temperature and its consequences on the electrical resistivity is essential to avoid misinterpretation of field measurements when considering resistivity acquisition at the same place but on different dates. Corrections can be then calculated, to express the electrical conductivity at the Standardized temperature of 25 C as follows (Samouëlian et al., 2005): .(4) where ótB is the conductivity at the experiment temperature, ó25 C the conductivity at 25 C, and á, the correction factor equal to 2.02%. where, n number of test points r o2m mean resistivity of subsoil in measurement point I, given in (Ùm). At each test centre point, geotechnical borings were made and lithologs obtained for comparison with the predicted geo-electric ground models from the VES. The apparent resistivity for each depth of probe was computed for the data sets for each electrode configuration. Apparent resistivity for depth windows 0-3m and 0-10m were averaged to represent shallow underground use in line with current practice and potential design depths for possible future infrastructure. The geospatial distribution of each set of apparent resistivity was generated using Surfer-16, and overlain on Google-Earth Pro for enhanced location visualization. Results and Discussions Fig. 3: The Schlumberger array for Vertical Electrical Sounding Fig. 4: Wenner-electrode configuration The results are presented as apparent resistivity maps corresponding to the two targeted depths of soil layers. It is pertinent to mention that the variation in the spatial distribution of the soil resistivity is ascribed to a combination of influencing factors, including topography (elevation), water level and quality, soil type and soil physical property (Okiongbo, 2019). In Figure 5, approximate ground elevation above mean sea level captured from a GPS shows a gradual decent to the
276 Atlantic coastline. Results of the spatial distribution of averaged superficial soil (0-3m and 0-10m below ground surface) resistivity are indicated in Figures (69). Figure 6 covers the Niger delta, where the resistivity ranges from 0-3500 ohm-m, and therefore has broadly grouped the areas of corrosion vulnerability and concern into a single class. Figure 7 on the other hand, covers a smaller area in sections of Rivers and Bayelsa States, and attempts to reduce the interval scale to 10 ohm-m in order to capture ground resistivity variations in line with the BS-1377 Journal of Mining and Geology Vol. 57(2) 2021. and Safway (2018) classification schemes. This figure clearly delineates the boundaries between the different categories of corrosion vulnerability as indicated by BS1377, in harmony with Safway (2018). Results of the spatial distribution of resistivity averaged over 0-10m below ground surface are presented in Figures (8 and 9). Figure 8 covers the Niger delta, where the resistivity ranges from 0-9,000 ohm-m, and as in Figure 6, also broadly grouped the areas of corrosion vulnerability and concern into a single class. Fig. 5: Distribution of Surface Elevation (m)-above mean sea level Fig. 6: Spatial variation of Apparent Resistivity averaged over (0-3m) for 0-3,400 ohm-m
Journal of Mining and Geology Vol. 57(2) 2021. 277 Fig. 7: Spatial variation of Apparent Resistivity averaged over (0-3m) for 0-250 ohm-m Fig. 8: Spatial variation of Apparent Resistivity averaged over (0-10m) for 0-9,000 ohm-m In order to achieve greater resolution in the delineation of the corrosion vulnerable zone, the scale was reduced to 0-250 ohm-m (Figure 9). A linear profile of soil resistivity across the Nigger delta from Cawthorne Channel to Obrikom had been reported by Abam (2016) in which averaged soil resistivity for 03m and 0-10m were effectively compared (Figure 10). Fortunately, this profile also traversed different geomorphic zones, and established typical values for each geomorphic zone. Fig. 9: Spatial variation of Apparent Resistivity averaged over (0-10m) for 0-250 ohm-m
278 As expected, the lowest resistivities are recorded in the mangrove swamps with the combination of high salinity, high water level and preponderance of silty and organic clay, confirming earlier findings (Osakuni and Abam, 2004; Okiongbo, 2019 ). There is also a distinctive increase with depth as shown by the Journal of Mining and Geology Vol. 57(2) 2021. difference in apparent resistivity between the 0-3m and that of 0-10m depth profiles. This difference is nonexistent in the other areas because of the near homogeneous composition of the soil and fairly consistent groundwater level. Fig. 10: Apparent Resistivity of surface layers (0-3m and 0-10m) along the traverse in the Eastern Niger delta According to Afa and Ngobia (2013), soil resistivity in Bayelsa State was found to be corrosive in most part of the state. Superficial soil resistivity ranged between 1 – 439 ? m, and over 70% of the resistivity values are within the moderately or very strongly aggressive category. This geomorphic zone is moderately aggressive (effective aggressivity); the few areas that are non-aggressive are localized. The results further indicated that resistivity of the superficial soils across the geomorphic zones in the Niger Delta generally decreases in a North – South trend, but with a slight increase at the beach ridges, perhaps due to the granular and significant fresh water presence. The observed trend in the variation of resistivity indicates the increasing trend of soil corrosivity in the north-south direction. Corrosivity increases from the undulating coastal plain lowland through the gentle lowland flood plains of the fresh water swamp, the coastal creeks, the meander belts, backswamps (depressions behind river levees that are subject to seasonal floods), down to the salt water mangrove and estuary complex, and truncates at the coastal beach ridges. The results of this study show that areas with higher elevation tend to have higher resistivity values as the ground is generally drier (Okiongbo, 2019). Furthermore, results show that the most severe corrosive sub-environments are at low elevations in poorly drained soils (e.g. salt water and mangrove swamp estuary complex, coastal creeks, meander belts and wooded back swamps and coastal beaches and Islands) such as clays and tidal marshes and in this respect are consistent with the findings of Schwerdtfeger (1965), Afa and Ngobia (2013). There is also a degree of season dependence of resistivity. This is evidenced by recording of consistently higher resistivity values during the dry season at three locations in Brass, Amassoma and Ogbia by Afa and Ngobia (2013). However, the effect of seasonal influence diminished with depth and disappears completely below the water table. The soil type, physical property of the soils and groundwater quality, are also in part, responsible for the observed spatial variability in resistivity (VillalobosAragón et al., 2019). The coastal plain lowland and lower flood plains of the freshwater swamps consists of soil types that are red ferralsols and dry, soft-firm-stiff, reddish yellow-brown-grey podzol overlying loose coastal sands exhibited relatively high resistivity due to interplay of low moisture regime, low degree of saturation, presence of non conductive iron oxide in the soil. The relatively low soil resistivity in the coastal creeks, meander belts, and wooded backswamps which are characterized by riverine and lacustrine deposits is on account of the very high water table, high saturation, preponderance of soft clay in the soils. The salt water mangrove swamps and estuary complexes geomorphic zone which registered the lowest resistivity values are characterized by soils rich in organic matter, consisting of very soft-soft peaty and bog soil, dark-grey-black organic clay, overlying fine sand deposits. Peaty and bog soils are poorly drained soils rich in organic matter with high humic acid concentrations that results in a high acidity level in the soil responsible for the high aggressivity of the soil. This combination of conditions results in high water saturation, thus enabling high ionic mobility. Furthermore, not only is the water table encountered at shallower levels as surface elevation decreases from the coastal plain sands sub-environment at the north of the delta to the coastal beach ridges at the coastline, but the
Journal of Mining and Geology Vol. 57(2) 2021. water quality changes from more conductive saline water in the predominantly mangrove areas to freshwater in the northern section of the delta. The comparatively higher resistivity values recorded in the coastal plain, lower flood plain, meander belts and wooded backswamps are essentially a reflection of the water quality. It is further observed that sections of the Mangrove swamp receiving freshwater discharge from the main river systems recorded slightly higher resistivity values compared to the mangrove soils with no direct link to freshwater discharge (Villalobos-Aragón et al., 2019). It 279 is probable that freshwater influxes into the sediments such mangrove swamp areas reduce the salinity of soils and by extension increase their resistivity. This argument is supported by a comparison of resistivity values of the mangrove swamps in the areas of significant freshwater discharge from the Niger River (Figure 11). A comparison of the slightly higher resistivity values around the Mangrove swamp receiving freshwater influxes from Brass/Nun River and those immediately to the right which receive little or nothing from the Niger River system, being not connected to it. Fig. 11: Flux efficiency ratios for rivers in the Niger Delta, Pre-Dam (1961) and Post-1998 Conclusion This study has shown that soil resistivity is the most reliable predictor of corrosion. It further shows that soil resistivity is largely influenced by the depositional environment as each geomorphic zone post depth averaged resistivity values within a narrow range. The study reveals that Corrosivity generally increases from the coastal plain sands to the mangrove swamps in the coastal zone. This implies that corrosion hazard is likely to be comparatively more rampart in mangrove swamp soils. By extension, it follows that buried metallic structures in the mangrove swamp will have a higher probability of degradation and therefore shorter design life expectancy.
Journal of Mining and Geology Vol. 57(2) 2021. 280 References Abam, T.K.S. (2016). Engineering Geology of the Niger Delta. Journal of Earth Sciences and Geotechnical Engineering, 6(3), 65-89. Adeniji, A. E., Omonona, V. O., Obiora, D. N., Chukudebelu, J. U. (2014). Evaluation of soil corrosivity and aquifer protective capacity using geoelectrical investigation in Bwari basement complex area, Abuja. Journal of Earth System Science, 123(3), 491–502. / 0491- 0502 Afa, J.T., Anaele, C.M. (2010). Seasonal Variation of Soil Resistivity and Soil Temperature in Bayelsa State. American Journal of Engineering and Applied Sciences. 3(4), 704 – 709. Afa, T.J. and Ngobia, O.F. (2013). Soil characteristics and substation earthing in Bayelsa state. European Scientific Journal, 9(9). https://doi.org/10.19044/esj.2013.v9n9p%p Agunloye, O. (1984). Soil aggressivity along steel pipeline route at Ajaokuta, South-Western Nigeria. Nigerian Journal of Mining and Geology, 21(1-2), 97-101. Allen, J.R.L. (1965). Late Quaternary Niger Delta and adjacent areas: sedimentary environments and lithofacies. American Association of Petroleum Geologists, 49, 549 – 600. Amobi C.E., Alexander I.O. and Obialo S.O. (2018). Geoelectrical study of corrosivity and competence of soils within Uburu and Okposi areas of Ebonyi State, Southeastern Nigeria, AntiCorrosion Methods and Materials. https:// doi.org/10.1108/ACMM-05-2018-1936 Bradford, S.A. (2000). Practical handbook of corrosion control in soils; Pieplines, tanks, casings, cables. Edmonton, Canada: Casti Publishing Ltd. Burger, H.R. (1992) Exploration Geophysics of the Shallow Subsurface. United States: Prentice Hall. Burton, R.G.O. (2001). Investigation of soils in Thames Water excavations, North London (January and March 2001). A report for Thames Water Utilities. NSRI, Cranfield University, UK (unpublished). Corcoran, P., Jarvis, M.G., Mackney, D. and Stevens, K.W. (1977). Soil corrosiveness in South Oxford. Journal of Soil Science, 28, 473 – 484. Doi: 10.5923/j.geo.20160601.02. Daryono, L.R., Rahmadani, H. R. and Suryanto, S. (2018). Spreading corrosion-model of selfpotential methods, Case study of buried metal laboratory scale. Asian Journal of Applied S c i e n c e s , 6 ( 6 ) . D o i : https://doi.org/10.24203/ajas.v6i6.5567 Ekine, A.S. and Emujakporue, G.O. (2010). "Investigation of corrosion of buried oil pipeline by the electrical geophysical methods", Journal of A p p l i e d S c i e n c e s a n d E n v i ro n m e n t a l Management, 14(1), 63-65. Ekoh, J.E., Akpabio, E.J. and Etukudo, U.I. (2012). Cathodic protection of buried pipelines
environments, the soil resistivity testing data provides an outstanding basis for assessing soil corrosivity. Table 1 shows a correlation of soil resistivity with soil corrosivity. The British Standards (BS-1377) formulated a classification system for soil aggressivity, here merged with corrosion specification by (Table 2).
III. Determination of Earth Resistivity in Multilayer Soil Model Uniform soil model (single-layer soil model) and the two-layer soil model are the most commonly used soil models for resistivity analysis. When there is a little variation in apparent resistivity, that model can be considered as a homogeneous/ uniform soil model.
Resistivity is also sometimes referred to as "Specific Resistance" because, from the above formula, Resistivity (Ω-m) is the resistance b Soil Resistivity In the USA, a measurement of -cm is used. (100 -cm 1 -m) 1.3 MAKING A MEASUREMEN the soil is required. The procedure and result interpretation. 1.3.1 PRINCIPLES Soil resistivity va
Moisture content, temperature and salts also affect soil resistivity. Soil that contains 10% moisture by weight will as much as five times lower soil resistivity than that which contains 2.5%. Soil at room temperature will be as much as four times lower in resistivity than that at 32 degrees. So the time of year that you conduct the test can
Moisture content, temperature and salts also affect soil resistivity. Soil that contains 10% moisture by weight will as much as five times lower soil resistivity than that which contains 2.5%. Soil at room temperature will be as much as four times lower in resistivity than that at 32 degrees. So the time of year that you conduct the test can
6 Resistivity Profiling for Mapping Gravel Layers, Amargosa Desert Research Site, Nevada resistivity soundings and multielectrode resistivity profiling. Models selected from the resistivity data are presented and interpreted, with particular attention to resistivity sections produced from the multielectrode transect measurements.
5.1 Soil resistivity measurements Soil resistivity is very important factor for earthing system designing so more attention required while measuring soil resistivity. The resistivity of soil varies appreciably with depth and also horizontally, it is often desirable to use an increased range of probe spacing on order to obtain an
where r is the soil apparent resistivity in Wm and k is a geometric parameter. This apparent soil resistivity r (1) is usually lumped and located at a depth D/2 between the electrodes, D being the electrodes' spacing (in meters). The above soil resistivity principle is also applied to a different and improved electrode arrangement, the Wenner .
Alfredo López Austin). Co-Edited Volume: Art and Media History –––Modern Art in Africa, Asia and Latin America: An Introduction to Global Modernisms. Boston: Wiley-Blackwell, 2012 (Elaine O’Brien, editor; Everlyn Nicodemus, Melissa Chiu, Benjamin Genocchio, Mary K. Coffey, Roberto Tejada, co-editors). Exhibition Catalogs ––– “Equivocal Documents,” in Manuel Álvarez Bravo (c
