See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/274251346 Pertophysical Characterization of Eight Wells from Wire-Line Logs, Niger Delta, Nigeria Article  in  Asian Journal of Applied Sciences · May 2014 CITATIONS 10 READS 295 4 authors: Some of the authors of this publication are also working on these related projects: EFFECT OF ENERGY SOURCE CHARGE SIZE AND DEPTH OF BURIAL ON SEISMIC EXPLORATION SEISMOGRAM QUALITY View project Shallow Geophysical Applications View project Idara Akpabio University of Uyo 31 PUBLICATIONS   209 CITATIONS    SEE PROFILE Johnson Ibuot University of Nigeria 56 PUBLICATIONS   265 CITATIONS    SEE PROFILE Okechukwu Ebuka Agbasi 71 PUBLICATIONS   311 CITATIONS    SEE PROFILE Odunayo Tope Ojo University of Uyo 4 PUBLICATIONS   11 CITATIONS    SEE PROFILE All content following this page was uploaded by Okechukwu Ebuka Agbasi on 30 March 2015. The user has requested enhancement of the downloaded file. Asian Journal of Applied Sciences (ISSN: 2321 – 0893) Volume 02 – Issue 02, April 2014 Asian Online Journals (www.ajouronline.com) 105 Pertophysical Characterization of Eight Wells from Wire- Line Logs, Niger Delta, Nigeria Akpabio Idara 1 , Johnson Cletus Ibuot 2 , Okechukwu Ebuka Agbasi 3 and Odunayo Tope Ojo 4 1 University of Uyo, Uyo, Akwa Ibom State. Nigeria Email: idarakapbio {at} yahoo.com 2 University of Uyo, Uyo, Akwa Ibom State. Nigeria Email: ibuotjohnson {at} yahoo.com 3University of Uyo, Uyo, Akwa Ibom State. Nigeria Email: ebukasean09 {at} yahoo.com 4 University of Uyo, Uyo, Akwa Ibom State. Nigeria Email: ojodunayo {at} yahoo.com _________________________________________________________________________________ ABSTRACT— Well log data from eight wells located in the X fields of the Niger Delta Basin were used in the determination of some Petrophysical characteristics of the reservoir sands. Well log data were obtained from sonic, gamma-ray, matrix density and resistivity logs. The Petrophysical characteristics investigated were porosity, water saturation, tortuosity and permeability. The results of the analysis revealed the presence of different sand and shale units. The thickness of each sand unit was highly variable, ranging between 6.1 and 21.5 m. Average porosities vary between 25.0 and 72.0 percent and generally decreasing with depth. A modeled water saturation showed a better value for water saturation (calculation) for non-Archie media. The correlation between the modeled water saturation method (using a different value of cementation factor m and tortuosity a as given by some literature) gives a weaker correlation for the non-Archie media while the Archie media gives a stronger correlation when compared with the Archie equation. The average water saturation of these units varied between 5.0 and 64.0 percent. These values are generally high for the sand units in varying wells. Similarly, the average permeability values varied between 22.0 and 70.0 mD. The results of this study will enhance the proper characterization of the reservoir sands and a better estimation of hydrocarbon saturation. Keywords— Porosity, Water Saturation, Hydrocarbon Saturation and Formation Factor _________________________________________________________________________________ 1. INTRODUCTION In the evaluation of a clastic reservoir, the presence of clay particles or shale within the sand is a parameter which must be considered. Shaliness is known to affect both formation characteristic and logging tool response. Carbonates, non-clastic reservoirs, are characteristically limestone and dolomite. Their importance as reservoirs rocks should not be under estimated. Approximately, 50% of hydrocarbon reservoir is a carbonate rocks ( Schlumberger, 1985). Well logging tools respond primarily to the chemical nature of matrix and pore fluids. In his pioneering work Archie ( Archie, 1950) sets out the fundamentals of rock- type classification. Any porous network is related to its host rock fabric, therefore Petrophysical parameter, such as porosity (ɸ), permeability (K) and saturation (S), for any given (type of rock) are controlled by pore sizes and their distribution and interconnection. The goal of reservoir characterization is to predict the spatial distribution of such Petrophysical parameter on a field scale. Archie (Archie, 1950) stated that a broad relationship exists between porosity and permeability of a formation. Petrophysics also refer to the careful and purposeful use of rock physics data and theory in the interpretation of reservoir geophysics observation (Lucia, 1983). This paper aimed at computing and evaluating the Petrophysical parameters of e i g h t in the Niger Delta using geophysical well log data. 2. LOCATION AND GEOLOGY AREA The Cenozoic Niger Delta is situated at the intersection of the Benue Trough and the South Atlantic Ocean where a triple junction developed during the separation of the continents of South America and Africa in the late Asian Journal of Applied Sciences (ISSN: 2321 – 0893) Volume 02 – Issue 02, April 2014 Asian Online Journals (www.ajouronline.com) 106 Jurassic (Whiteman, 1982). Subsidence of the African continental margin and cooling of the newly created oceanic lithosphere followed this separation in early Cretaceous times. Marine sedimentation took place in the Benue Trough and the Anambra Basin formed-Cretaceous onwards. The Niger Delta started to evolve in early Tertiary times when clastic river in put increased (Doust, and Omatsola, 1990).Generally the delta prograded over the subsidizing continental- oceanic lithospheric transition zone, and during the Oligocene spread on to oceanic crust of the Gulf of Guinea (Adesida, Reijers, Nwajide, 1997). The weathering flanks of out-cropping continental basement sourced the sediments through the Benue-Niger drainage basin. The delta has since Paleocene time’s prograded a distance of more than 250km from the Benin and Calabar flanks to the present delta front (Evamy, Hammering, Kmoap, and Rowland, 1978). Thickness of sediments in the Niger Delta averages 12km covering a total area of about 140,000km2. The Stratigraphic sequence of the Niger Delta comprises three broad lithostratigraphic units namely, (1) a continental shallow massive sand sequence the Benin Formation, (2) a coastal marine sequence of alternating sands and shales the Agbada Formation and (3) a basal marine shale unit-the Akata Formation. The Akata Formation consists of clays and shales with minors and intercalations. The sediments were deposited in pro delta environments. The sand percentage here is generally less than 30%. The Agbada Formation consists of alternating sand and shales representing sediments of the transitional environment comprising the lower delta plain (mangrove swamps, floodplain, and marsh) and the coastal barrier and fluviomarine realms. The sand percentage within the Agbada Formation varies from 30 to 70%, which results from the large number of depositional off lap cycles. A complete cycle generally consists of thin fossil ferrous transgressive marine sand, followed by an off lap sequence which commences with marine shale and continues with laminated fluviomarine sediments followed by barrier sand/or fluviatile sediments terminated by another transgression (Weber, 1972; Ejedawe, 1989). The Benin Formation is characterized by high sand percentage (70 – 100%) and forms the top player of the Niger Delta depositional sequence. The massive sands were deposited in continental environment comprising the fluvial realms (braided and meandering systems) of the upper delta plain. 3. MATERIAL AND METHOD The data collected from the eight (8) fields in the Niger Delta is related geological data, routine core analysis (permeability, porosity, cementation exponent, saturation exponent) and well logging data, including gamma ray, resistivity, density and neutron logs which were collected and reviewed. Well logging interpretation provides the output of log analysis in term of reservoir parameter. Quick look log interpretation is generally used in formation evaluation using well logs. This interpretation method provides the information which help geologists, geophysicists, reservoir engineers and drilling engineers in short time. Basically, it relies on overlays of logs, interpretation charts, or graphic methods such as cross plots to minimize methods requiring detailed calculation. The interpretation can derive porosity, water saturation from available well logging data. The zones of reservoir can be identified by many parameters. The permeability is determined from permeability porosity relationship from core analysis of the corresponding well. Zone of reservoir is determined by gamma ray and resistivity logs. Make cross plot GR to separate shale and sand lines. Resistivity log is fundamental in formation evaluation because hydrocarbons do not conduct electricity. Therefore, the well logs are split into interval of porous and non-porous rock, permeable and non-permeable rock or shaly and clean sand rock. The clean sands and sandstones are determined by GR log are low radioactive because GR log records the abundance of the radioactive isotopes of thorium, uranium and potassium. They are usually concentrated in shales and less concentrated in sandstones, so high GR reading can be observed normally and can be used as regional marker because shale is deposited in wide area. Resistivity curve can indicate hydrocarbon in porous and permeable rock. The sonic tool is selected to calculate the porosity in a good borehole condition. The Sonic log is used as porosity method, the equation to calculate the porosity based on the sonic log is as follows: b sb b p V VV V V   Where ɸ = fractional porosity Vp = Pore Volume Vb = Bulk Volume Vs = Gain Volume Formation factor can obtain Rw. When a given zone is water bearing that Rt reverts to the water bearing resistivity (Ro). Therefore, a number of water zones can be plotted depth versus Rw from calculation w o R R F  F = formation resistivity factor or simply formation factor Asian Journal of Applied Sciences (ISSN: 2321 – 0893) Volume 02 – Issue 02, April 2014 Asian Online Journals (www.ajouronline.com) 107 Ro = resistivity of rock when water saturation is 1 (100% saturated) Rw = resistivity of saturating water m a F   Φ = porosity a = empirical constant (default = 1) m = cementation exponent (default = 2) For determination of water saturation of a clean sand formation we use the following equations t on w R R S  Sw = water saturation Rt = resistivity of rock when Sw < 1 Ro = resistivity of rock when water saturation is 1 (100% saturated) Combining the above equations gives Archie’s equation, the most fundamental equation in well logging. t w m t wn w R FR R aR S   Practical average Archie’s Equation general equation for finding water saturation is 2/1 15.2 62.0          t w w R R S  Using proper m relationship determines permeability in the reservoirs. In-situ porosity versus logarithm of permeability can be plotted, and the relationship can predict more accuracy and be divided by facies and/or formation. PA Lq k    k = permeability of reservoir 4. RESULT AND DICUSSION The analysis of the eight wells, each of which is divided into three zones based on the porosity of each zone. In each zones of the wells, the formation of the wells was determined using the plot of Depth versus Gamma log. High gamma reading indicates shale formation while low gamma reading indicates sand formations. Porosities within the field are observed general to decrease with depth. The estimated average porosity value ranges between 0.82 and 0.22, decreasing with depth. These low porosity values may be attributed to mainly grain size and sorting effects within the reservoir sands. (Pickett, 1960; Beard and Weyl, 1973 and Scherer, 1987). All the sand units investigated are confined within the Agbada Formation. The varying shale contents and the depths of burial may have contributed, though to a minor extent, to the decrease in porosity. The porosity values are however considered to be fairly good for hydrocarbon accumulation. Average water saturation of the sand units vary between 0.05 and 0.52 for cementation factor (m = 1.8) and 0.05 and 0.64 for cementation factor (m = 2.0). These average water saturation values are observed to increase with depth. The average permeability values for the values for the various sand units vary between 0.70 and 0.27, for m = 1.8 and between 0.22 and 0.65, for m = 2.0. The thickness of the sand units is highly variable for both sand and shale formation, becoming thinnest around well 2, 6, 1, 7, 3, 5, 4, 8 and 9. The sand thickness for well 1 is between 13 – 32ft, well 2 between 20ft, well 3 between 32 – 60ft, well 4 between 45 – 47 ft, well 5 between 50ft, well 6 between 18 – 39ft, well 7 between 20 – 50ft, well 8 between 60 – 80ft and well 9 between 26 – 100ft. For Archie media the water saturation values for both the Archie and modeled equation, the correlation between both of them are strongly related having values of 0.99997 – 0.99999, while for non-Archie media they are less related having values of 0.99992 – 0.99995. Asian Journal of Applied Sciences (ISSN: 2321 – 0893) Volume 02 – Issue 02, April 2014 Asian Online Journals (www.ajouronline.com) 108 5. CONCLUSION Petrophysical analysis was carried out for all the identified hydrocarbon intervals, from the eight wells studied in the Niger Delta Fields using suites of geophysical well logs. From the analysis of the geological logs comprising gamma-ray and electrical resistivity, the total porosity in the hydrocarbon bearing zone was found to range from 25.0% to 75.0% and the water saturation range from 5.0 to 64.0%. Good well-to-well lithology correlation was established across the fields studied .The researcher found that the bulk of the hydrocarbon encountered in the Niger Delta basin was found to be within a depth range of 2,050 – 11,620ft (624.84 – 3,541.78m) as compared to the values gotten by Falebita, 2003 (about 1,200 – 3,650m) and Aigbedion, 2007 (about 2,510 – 3,887m). The hydrocarbon reservoirs were found to 0 0.2 0.4 0.6 0.8 1 7625 7630 7635 7640 7645 7650 7655 7660 7665 Sw a n d S h Depth (ft) Depth(ft) vs Sw and Sh Water Saturation(Sw) Hydrocarbon Saturation (Sh) 0 20 40 60 80 100 120 140 7625 7630 7635 7640 7645 7650 7655 7660 7665 So n ic (φ s) a n d G R ( g A P I) Depth (ft) Depth(ft) vs Sonic Log vs GR log SONIC (µs/ft) GR(gAPI) 0.4 0.42 0.44 0.46 0.48 0.5 0.52 0.54 7625 7630 7635 7640 7645 7650 7655 7660 7665 φ a n d k Depth (ft) Depth(ft) vs ɸ and k Porosity (φ) Connectedness Asian Journal of Applied Sciences (ISSN: 2321 – 0893) Volume 02 – Issue 02, April 2014 Asian Online Journals (www.ajouronline.com) 109 be in the Agbada formation, which is in conformity with the geology of the Niger Delta, Nigeria. This study was carried out to find out if the petrophysical parameters computed in the field will encourage deeper drilling in the area of study. One of the most important tasks in reservoir engineering is characterizing different parameters of the reservoir. Water saturation is a parameter which helps evaluating the volume of hydrocarbon in reservoirs. Determination of this parameter started from 1942 by integrating some well logs in clean sandstones. After that, many scientists introduced some equations to validate this procedure in shaly sands and carbonates (Lucia, 1983). To treat the problem of dependency of water saturation estimation on core analysis in previous works, other scientists proposed using rock physics and arrived at improved models of water saturation estimation. More recently, interpreters have used seismic attributes to evaluate water saturation values directly or estimating proper rock physical properties such as tortuosity which are useful in water saturation estimation process. 6. REFERENCES [1] Adesida, A.A., Reijers T.J.A, Nwajide C.S. (1997) Sequence stratigraphic framework of the Niger Delta. Paper presented at the AAPG international conference and exhibition, Vienna, Austria [2] Aigbedion, I., (2007). Reservoir Fluid Differentiation case study from the Oredo Field. International, Journal of Physical Sciences, 2 (6): 144-148. [3] Archie, G.E., (1950) Classification of Carbonate Rocks and Physical Consolidations. AAPG Bulletin, 36. [4] Doust, H., Omatsola, E. (1990). Niger Delta in divergent/passive margin basins, in J. D. Edwards. and P. A. Santogrossied, eds., Am. Assoc. Petrol. Geol. Memoir, 48: 201-238. [5] Ejedawe, J.E. (1989) The Eastern Niger Delta: geological evolution and hydrocarbon occurrences. SPDC Internal Report, Exploration Note 89. 002 [6] Evamy, D.D., P. Hammering, W.A. Kmoap and P.H. Rowlands, (1978). Hydrocarbon habitat of the tertiary Niger Delta. American Association of 1-3. Petroleum, Geologist Bulletin, 62(2): 1-10. [7] Falebita, B. (2003). Deep drilling in the Niger Delta. Nape bulletin. Vol 10(1). [8] Lucia, F.G., (1983). Petrophysical parameters estimated from virtual description of carbonate rocks. Journal of petroleum technology, Canada, 32: 49 -53 [9] Pickett, E. (1960). The use of acoustic logs in the evaluation of sandstones reservoir. Geophysics, 21(#3): 250 – 274. [10] Schlumberger Educational Services. 1985. “Log Interpretation Principles/Applications”. Schlumberger Manual. [11] Weber, K.J. (1972). “Petroleum Geology of the Niger Delta”. 9th World Petroleum Congress: Tokyo, Japan. 2:207-221. [12] Whiteman, I.K. (1982). Fundamental of Reservoir Engineering, 4th ed. University of Oklahoma Press, Norman, 426 pp. View publication statsView publication stats