Petrophysical Analysis of the Mpapai well Logs in the East Pande Exploration Block, Southern Coast of Tanzania: Geological Implication on the Hydrocarbon Potential

This study presents results of log analysis from Mpapai well, which is located in the East Pande Block, southern coast of Tanzania. The study aimed at assessing the hydrocarbon potential of lithological units encountered during drilling of Mpapai well. To achieve the general objective, suites of wire-line logs from Mpapai well were used for the analysis. Based on wire-line logs, three types of lithology were identified which include sandstone, shale and limestone. Seven sandstone bodies marked as MpapaiA, B, C, D, E, F and G were identified with their tops and bases at the depth interval from 3004 m to 4008 m. Four zones among seven sandstones bodies marked as MpapaiB, E, F and MpapaiG were identified as reservoir zones. Computed petrophysical parameters for the four reservoir zones gave an average total porosity ranging from 14% to 21% with low permeability in the range of 3.92 mD to 13.67 mD. The low permeability indicates that the reservoir sand bodies are impermeable, that might have been affected by the geology of the area where high content of clay minerals reduces permeability due to filling in open spaces. The fluid type defined in the reservoir zones is basically water with high saturation greater than 75%, which indicates that the proportion of void space occupied by water is high, consequently low hydrocarbon saturation and production. Despite of fair to good porosity, the low permeability and high-water saturation indicate that the quality of Mpapai prospect is poor.


Introduction
Southern coastal basins of Tanzania are located in the southern tip of the Somali basin, which is connected to the Natal basin in South Africa through the Mozambique Channel [1]. Petrophysical analysis of well logs is one among the most useful and important tools for reservoir rock characterization. It helps to define physical characteristics of rocks such as lithology, porosity, permeability and fluid saturation.
The analysis is also useful in identifying potential reservoir intervals, distinguishing the type of fluid in a reservoir and estimating hydrocarbon reserves [5] [6]. This study therefore aims at using well logs data to characterize sedimentary units of Mpapai well and to delineate potential reservoir formations based on petrophysical properties in order to assess the hydrocarbon potential of lithological units encountered during drilling of Mpapai well by using well logs data (gamma ray log, neutron porosity log, bulk density log, PEF values and resistivity logs).

General Geological Setting
The East Pande Exploration Block is one among the south-eastern Tanzania coastal basin located along the passive continental margins of western Indian Ocean developed on the Precambrian Pan-African basement [8]. Stratigraphically, the East Pande formation forms the upper part of the Kilwa group, which developed during the period of tectonic stability. The group can be broadly divided into lower and upper formations; the lower two (Nangurukuru and Kivinje) being predominantly claystone, while the upper two (Masoko and Pande) are unconsolidated clays [9].

Tectonic Setting
The geology of the area is strongly affected by two-stage break-up of Gondwana,

Sequence Stratigraphy of the Offshore Tanzania
The present sequence stratigraphic framework and architecture of offshore

Material and Methods
The study accomplished the objectives using well log data from Mpapai well

Lithology Identification
The identification of lithology is fundamental to all reservoir characterization because the physical and chemical properties of the rock that holds hydrocarbons and/or water affect the response of every tool used to measure reservoir properties [12]. Understanding reservoir lithology is the foundation from which all other petrophysical calculations are made. The best logs for lithology identification are those that are most influenced by rock properties and least influenced by fluid properties [13]. In this study, lithology across Mpapai well were identified using gamma ray (GR) log, photoelectric factors (PEF), neutron-density combination and cross plot as described in the following sub sections.

Lithological Identification from Gama Ray Log
Identification of lithology from gamma ray log was done by reading API values on the gamma ray curve which ranges from 0 to 150 API where the sand/shale baseline was inserted at 75 API in order to differentiate the two lithologies (sand and shale). Therefore, all formations with gamma ray values less than 75 API were classified as sandstone, while those with gamma ray values greater than 75 API were classified as shale.

Lithological Identification from Photoelectric Factor
In this study, classification of lithology was based on the values given in Table 1 [6], which shows the common lithology with their photoelectric values. Values were obtained by taking the average values from log curve across each lithology.

Lithological Identification from Neutron-Density Combination
Neutron and density logs were sketched together in the same track for doing some comparison and the correlation between the two curves leads to better lithology identification. When both the density and neutron logs show lower value, it indicates sandstone formation whereby overlay of the two log curves shows limestone lithology and the increase of neutron and density value indicates shale lithology.

Lithological Identification from Neutron-Density Cross plots
Neutron-density cross plots are easy to use for clean (non-shaly) reservoir rocks.
The plots are entered with a bulk density and apparent neutron porosity. A rock type (sandstone, limestone, or dolomite) and a corrected porosity can be read from the cross plot. The neutron-density cross plot was used to determine lithology of Mpapai well by plotting together neutron and density logs and use gamma ray log for scale. Points were observed to fall into different lithological regions and the interpretation of the lithology (sandstone, carbonate and shale) was based on color legend bar, which is the intensity of gamma rays. The gamma ray intensity represents the amount of concentration of the radioactive elements present in the neutron-density logs, thus giving different types of lithology.

Reservoir Identification
Reservoir is the only zone, which is potential for economic interest because it contains storage space for fluid (hydrocarbon or water) to accumulate. Thus, must first of all be identified in order to evaluate important parameters suitable for hydrocarbon exploration. Reservoir identification was conducted after the interpretation of various lithology of Mpapai well. The clean (non-shale) formation was marked in different zones as reservoir rocks. Reservoir rocks are defined as subsurface pool of hydrocarbon or water contained in porous or fractured rock formation [6]. Porosity and permeability are the most important physical properties of the reservoir rocks. For rock to be named a reservoir has to be porous and permeable. Sandstone (which covers 62% of the petroleum reservoir) and Limestone are two sedimentary rocks, which are used as reservoir rocks [5]. A good reservoir rock must be a good porous, permeable and contains hydrocarbon as well. In this study reservoir rock was identified using gamma ray log, resistivity log and neutron-density crossover.
Gamma ray log was used in the identification of reservoir rock based on the fact that, sandstone reservoir exhibits very low radioactivity because of low content of radioactive elements hence have low gamma ray value and the log deflect to the left of shale/sand baseline [12]. Resistivity logs (deep and medium) were also used to identify reservoir zone in the sense that, reservoir zones exhibit relatively higher resistivity values than non-reservoir zones. Based on neutron and density logs, reservoir rock was also marked by the presence of neutron-density crossover, which indicated the presence of fluid.

Fluid Identification
It is very important to identify the type of fluid in a reservoir rock, because reservoirs may contain hydrocarbon (oil and gas), non-hydrocarbon fluid (water) or both. For a reservoir to contain hydrocarbons the zone should be porous with resistivity values higher than those of water-bearing zones [14]. In this study, the resistivity log and neutron-density log were used to identify hydrocarbon and non-hydrocarbon bearing intervals. Hydrocarbons are poor conductors than water, hence show higher resistivity than water bearing interval. Based on neutron and density crossover, gas zone is expected to show wider negative separation due to low density and low hydrogen index of gas. Oil zone is also expected to show relatively low negative separation because of relatively high density and hydrogen index compared to gas. Very low separation is observed in water zone due to higher density and higher hydrogen index in water.

Shale Volume Estimation
The analysis of shale volume was conducted in order to determine the amount of shale or radioactive minerals, contained in the reservoir rock in order to delineate zones of interest. In this study, the volume of shale was estimated using Gamma ray logs and neutron-density methods. The method that gave the minimum value of shale volume was chosen for further estimation of porosity and water saturation in order to minimize the effect of reducing reservoir quality caused by high content of shale volume.

Shale Volume Estimation from Gamma Ray Logs
Gamma-ray log is one of the best tools used for identifying and determining the shale volume. This is principally due to its sensitive response on the radioactive materials, which normally concentrate in the shaly rocks. In this study, the first

Shale Volume Estimation from Neutron-Density Logs
The separation between neutron and density porosity is a common method for rock fragments. These minerals are heavier than quartz, which cause excess separation by reducing density porosity and increasing neutron porosity [14]. This method is also inaccurate when the reservoir contains gas, where it affects neutron reading by reducing the neutron porosity value due to low hydrogen index of gas. Despite all these precautions this method was also used to calculate shale volume because of the nature of the geology of the study area that sandstone at Mpapai well consists of clay minerals and fine to very fine angular sand grains [4]. Thus, the method could provide accurate shale volume. The following formula was used to calculate volume of shale from Neutron-Density log as [18]:

Porosity Evaluation
Porosity is very important parameter of the reservoir rock as it is used to describe the amount of open space filled with fluid (hydrocarbon or water). In this study, porosity was calculated from two methods, density log and density-neutron combination logs. The criteria used in classifying porosity are given in Table 2 [20] [21].

Porosity from Density Log
Density log is a good method for determining either total or effective porosity in single or multiple mineral fluid-filled reservoirs. The method of estimating porosity from the density requires determining the matrix density (ρ ma ), the density log reading (ρ b ), and the fluid density (ρ fl ) at the depth of interest. The matrix density is determined by the lithology. Normally, sandstone is 2.65 g/cm 3 , limestone is 2.71 g/cm 3 , and dolomite is 2.87 g/cm 3 [22], these values were also used in this study. The fluid density is dependent upon the salinity of water and the density of hydrocarbon. Freshwater has a density of 1.0 g/cm 3 and saltwater has approximately 1.1 g/cm 3 . Hydrocarbon density can vary widely from 0.05 g/cm 3 for gas at low pressures to nearly 1.0 g/cm 3 for certain oil. A typical value for oil is 0.8 g/cm 3 [23]. In this study, the porosity was also determined from density log using the formula below: where ϕ = Total porosity, ma ρ = Matrix density (or grain) density (2.65 g/cm 3 ), b ρ = Formation bulk density from log and f ρ = Fluid density (1.1 g/cm 3 ).

Porosity from Neutron-Density Combination
The combination of neutron and density logs provides a good source of porosity data, especially in formation of complex lithology. Better estimates of porosity are possible with this method than using other tool separately such as density and sonic because inferences about lithology and fluid content can be made.
Porosity from Neutron-Density log can be calculated mathematically using the following equation [12]: where N D φ − = Neutron-density porosity, N φ = Neutron porosity and D φ = Density porosity.

Water Saturation Determination
In this study, two models (the Archie's and Indonesian models) were used to calculate water saturation of the reservoir rocks and results were compared. The Archie's model works well in homogeneous or clean sand reservoir [24] while the Indonesian model work well in both clean sand and shaly sand reservoirs. In clean sand reservoirs both Archie's and Indonesian models provide nearly the same water saturation results, while for shaly sand reservoir Indonesian model provides good water saturation results [25].

Water Saturation from Archie's Equation Model
Archie's equation is most famous method for calculating water saturation in clean and Shale free formation. Archie formula is based on the fact that the only conductive material in the formation is salt water; but in a sandy shale formation, ions that are released along with shale are also responsible for conducting electrical current [26]. In this study, Archie's equation was used to calculate water saturation in all reservoir sections, and the results from shaly sand were compared from that of Indonesian model. To calculate water saturation w S from Archie's model, the following equation was used: where w S = Water saturation, w R = Formation water resistivity, ϕ = Total porosity, t R = True formation resistivity, a = Tortuosity factor, m = Cementation exponent and n = Saturation exponent.

Water Saturation from Indonesian Equation
Water saturation ( w S ) results from the formula are comparatively easy to calculate and because it is not a quadratic equation, it gives results that are always greater than zero. Calculation of water saturation by using this method depends on porosity, shale volume and resistivity, water and deep resistivity. Water saturation from Indonesian model is given by the following formula: where sh V = Volume of shale, sh R = Resistivity of shale, w S = Water saturation, e φ = Effective porosity, w R = Water resistivity of formation, m = Cementation coefficient, n = Saturation capacity and t R = Real resistance.

Determination of Hydrocarbon Saturation
Hydrocarbon saturation h S is the percentage of pore volume in a formation occupied by hydrocarbon. In this study, the hydrocarbon saturation was determined by subtracting the value of water saturation from 100%, as illustrated in the equation below:

Permeability Estimation
Well log is one among the methods used to estimate permeability of a reservoir rock. There are two principal log measurements used to estimate permeability, these are resistivity and porosity logs. Porosity log is frequently preferred than resistivity log because it is strongly correlated to permeability [6]. In petrophysics various empirical models were established for permeability estimation, these include model by Tixier [27], Wyllie and Rose [28], Timur [29], Coats and Dumanoir [30], Coats and Denoo [31]. The classification of these models was based on grain size, pore dimensions, mineralogy and surface area, or water saturation [6] [32]. In this study, the Timur [29] model was used to estimate the permeability of each delineated reservoir rocks of Mpapai well. This method depends on porosity and irreducible water saturation as shown in the equation below [23]: where K = Permeability in mD, φ = Porosity and wir S = Irreducible water saturation Irreducible water saturation was estimated from Crain's method [33] using the equation below [34]: different depths are constant, they indicate that the reservoir zone is at irreducible water saturation otherwise the reservoir zone is not at irreducible water saturation [12]. Permeability of reservoir rocks is qualitative and the qualitative description used in this study is given in Table 3 (Rider, 1986;Baker, 1992).  Table 4). Generally, the stratigraphy of Mpapai well shows the composition of alternating sand and shale layers ( Table 4). The thicknesses of shale layers are observed to increase with depth along with a corresponding decrease in sand layer. In some intervals the sandstone formations are cemented by carbonate cement.

Reservoir Identification
From the four chosen depth intervals shown in the previous section, seven clean sand bodies were identified across Mpapai well, which were named as MpapaiA, B, C, D, E, F and MpapaiG. Generally, based on visual observation of well logs, zones that showed low gamma ray values, relatively high porosity and high resistivity values were identified as reservoir zones. Therefore, only four sandstone bodies named MpapaiB, E, F and MpapaiG among seven identified zones were marked as reservoir zones (Figure 8 and Figure 9). These zones were also characterized by neutron-density crossover showing wider separation, which indicate the presence of gas.

Hydrocarbon and Non-Hydrocarbon Bearing Zones
The neutron-density logs combination and resistivity logs were used for the identification and characterization of various fluids in the reservoir zone. Based on visual observation of these logs four selected reservoir zones named MpapaiB, E, F and MpapaiG among seven selected reservoir zones were identified as gas bearing zones. This is due to the presence of neutron-density crossover and     high resistivity values. Neutron and density crossover were observed in some intervals and marked by yellow color as shown in the log curves for MpapaiB, E, F and MpapaiG respectively (see . In resistivity logs, values in the reservoir zones were observed to be relatively higher, which also indicate the presence of hydrocarbon. As described in methodology part, resistivity logs are commonly used to differentiate types of hydrocarbon fluids in the sense that liquid hydrocarbon normally display higher resistivity values compared to gas zones. Based on these observations, the type of hydrocarbon fluid that could be found in these reservoirs is gas.        Figures 10-13). The water saturation values suggest that reservoir zones are water bearing with low hydrocarbon saturation (1.6% to 35.9%). The average permeability was observed to be fair to moderate with average values ranging from 3.9 mD to 11.2 mD (see Table 3; Figures  10-13).

Assessment of Petrophysical Parameters from Qualitative Interpretation
The petrophysical analysis of Mpapai well on identification of lithology indicates that the well consists of three types of lithology, which are shale, sand and very little carbonate. The most dominant lithological unit encountered at Mpapai well was shale formation with thickness ranging from 7 m to 716 m. These shale units as described in the study by Nicholas et al. [4] forms claystone or muddy clays, which develop a mild shaly parting. Sandstone formation was also identified with thickness ranging from 3.8 m to 36.58 m and in some intervals sandstone formation was interbedded with thin shale beds. Anomalous peaks in gamma ray log together with the overlay of neutron and density curves indicate the presence of carbonate formation. Neutron-density cross plot strongly show the presence of carbonate formation. In most cases carbonate formation (limestone) occurs as cement in sandstone formation. Stratigraphic log curves show that Mpapai well consists of alternating sand and shale layers. The shale layers were observed to increase with depth along with a corresponding decrease in sand layers. Based on well log analysis, a total of seven clean sand formations were identified, which were named as MpapaiA, B, C, D, E, F and MpapaiG. Of the seven sandstone bodies, four reservoir zones with high resistivity values and the presence of neutron-density crossover were identified. These include MpapaiB (3.8 m thick), MpapaiE (36.58 m thick), MpapaiF (5.55 m thick) and MpapaiG (38.69 m thick). The reason for categorizing the four sand units as different reservoir zones was based on eliminating thick shale beds between reservoirs so as to reduce the effect of increasing shale volume when computing other petrophysical parameters. The shale formation between the identified reservoirs could thus be interpreted as source rock when located below reservoir rock and as a seal rock when located above the reservoir rock.

Assessment of Petrophysical Parameters from Quantitative Interpretation
The four selected reservoir zones were analyzed quantitatively to estimate the values of shale volume, porosity and water saturation by using empirical formulas as described in the methodology part. After applying cutoff values of 0.5 shale volume, 9% porosity and 50% of water saturation, the net pay thicknesses for the four selected reservoir zones of MpapaiB, E, F and MpapaiG were found to be 2.90 m, 5.18 m, 1.37 m and 26.52 m respectively ( Table 2). The average shale volume estimated from gamma ray log was found to be 0.055 v/v, 0.077 v/v, 0 v/v and 0.079 v/v for MpapaiB, E, F and MpapaiG respectively (Table 5). Based on these estimates reservoir zones were interpreted as clean sand reservoirs. The total and effective porosity results of the delineated reservoir zones vary widely ranging from 14% to 21%, which indicate that the reservoir quality ranges from fair to good porosity (e.g., [20] [21]). Saturation results indicate that more than 75% of Mpapai prospect consists of water in which the average value of water saturation for each reservoir zone was found to be 86.3% for MpapaiB, 75.3% for MpapaiE, 64.1% for MpapaiF and 98.4% for MpapaiG. The water saturation indicates that the proportion of void space occupied by water is high consequently low hydrocarbon saturation and low hydrocarbon production.

Geological Implication on the Petrophysical Parameters
Generally the quality of reservoir zones of Mpapai well is strongly affected by both local and regional geology of the area. Locally, the East Pande Block is highly composed of clays with very fine grains [4], which tend to fill in open spaces between courser grains (sand particles). This eventually reduces porosity and permeability, which are the key parameters for a good reservoir rock (e.g., Open Journal of Geology

Conclusion
Generally, by considering all parameters such as reservoir thickness, shale volume, porosity, permeability, water saturation and hydrocarbon saturation from the log analysis performed in this study, the quality of the reservoir sand units of Mpapai well is poor. Some reservoir zones (MpapaiB and F) are very thin, which also reduce the quality of reservoir zones if they do not extend lateral. Selected reservoir zones have an average porosity ranging from fair to good. MpapaiB has good porosity of 21% while MpapaiE, F and G have fair porosity of 14%, 15% and 16% respectively. Permeability obtained from this analysis is fair indicating that the reservoir sand bodies are impermeable that might have been affected by the geology of the area where high degree of compaction, cementation (presence of carbonate cement in sandstone formation) and high content of clay minerals reduces permeability due to filling in open spaces. The quality of the reservoir zones is also poor due to low hydrocarbon saturation in which more than 75% of the reservoir zones are filled with water. The water saturation indicates that the proportion of void space occupied by water is high consequently low hydrocarbon saturation and low hydrocarbon production.