Petrophysical properties assessment using wireline logs data at well#3 of Srikai

Md.Shhdot Hossin, M.Moklesur Rhmn,*, Mst.Hbib Khtu, Md.Rubel Hque

a Department of Petroleum and Mining Engineering, Jashore University of Science and Technology, Jashore 7408, Bangladesh

Keywords: Srikail gas field Multiple wireline logs Reservoir petrophysical properties Quantitative values Gas field development Bangladesh

ABSTRACT This study focused on the quantitative analysis of the petrophysical parameters in characterizing the reservoir properties of the Srikail gas field using multi-scale wireline logs.Petrophysical parameters (shale volume, porosity, water saturation and hydrocarbon saturation) were estimated from the combination of gamma ray log, resistivity log, density log and neutron log for three hydrocarbon (gas)-bearing zones at well#3.At the first time, log records at 0.1 m and 0.2 m intervals were read for this study.Result showed the average shale volume is 21.07%, 53.67% and 51.71% for zone-1, zone-2 and zone-3, respectively.For these zones, the estimated average porosity was 35.89%, 29.83% and 28.76%, respectively.The average water saturation of 31.54%, 16.83% and 23.39% and average hydrocarbon saturation of 68.46%, 83.17%and 76.61% were calculated for zone-1, zone-2 and zone-3, respectively.Thus zone-2 is regarded the most productive zone of well#3.It was found that the values of some parameters (porosity, hydrocarbon saturation and permeability) are higher than the existing results.Therefore, this study confirmed that the log reading at minute/close interval provides better quantitive values of the reservoir’s petrophysical properties.It is expected that this result will contribute to the national gas field development program in future.

1.Introduction

Conventionally, petrophysical characterization involves the assessment of chemical and physical rock properties and their interactions with fluids contents in the reservoir (Iqbal R et al., 2017).Petrophysics is mostly utilized for the study of hydrocarbon reservoir characterization.In order to understand the rock properties such as how pores in the formations are interconnected, controlling the fluid accumulation and migration and their interactions with the pore fluids,petrophysical properties are utilized (Kumar M et al., 2018).The common and significant properties assessed in petrophysics are the formation lithology, its porosity,permeability, density, water saturation and resistivity (Iqbal R et al., 2017).Thus the presence of hydrocarbon in a reservoir depends on the function of its petrophysical properties mostly on porosity and its hydrocarbon saturation (Ahammod S et al.,2014).The presence of porosity of any hydrocarbon-bearing formation illustrates the qualitative description of the reservoir (Table 1).

The integration of multi-scale data such as seismic surveying data, well logs data and surface and subsurface geological data is essential for the evaluation of petrophysical properties as well as the characterization of hydrocarbon reservoirs (Al Fatta A et al., 2018; Serra O, 1984).

However, for the assessment of hydrocarbon reservoir characteristics, well logging is the widely used techniques trough out the globe because well logs provide continuous,uniform and considerable quality data from top to bottom of different zones along the well.Moreover, well logs are costeffective, time-effective and practical techniques in the petroleum industry for the quick measurement of reservoir properties.In addition, the data retrieved from the well logs play a crucial role in the measurement of the production potential of a hydrocarbon reservoir (Ellis DV, 1987).Therefore, good quality well logging data is essential for the petrophysics study and in turn to reservoir characterization.Since the beginning of the petroleum industries, acombination of multiple geophysical well logs such as gamma-ray (GR) log, self-potential (SP) log, resistivity log,neutron log, sonic log and density log are widely used to define the physical characteristics of the reservoirs such as shale volume, porosity, water saturation and hydrocarbon saturation (Das B and Chatterjee R, 2018; Islam A et al.,2013).Moreover, the petrophysical properties retrieving from the conventional well logs have been using for developing various computer-based models such as neural network modeling in order to characterize the reservoirs (Pandey AK et al., 2020; Gogoi T and Chatterjee R, 2019).The objective of this study is to evaluate the petrophysical properties of the hydrocarbon reservoir at Srikail gas field, Bangladesh using the combination of the gamma-ray log, different types of resistivity log, sonic log and neutron logs available for well#3.

Till now, there are 27 gas fields in Bangladesh (Table 2).As a fast-growing country, the demand for energy in Bangladesh increases drastically.Hydrocarbon more specifically natural gas is the main source of energy.The initial estimated recoverable gas reserve was around 12.43 TCF (Shetol MH et al., 2019) in 1993.By the re-estimation,the amount increased to around 26.84 TCF by 2011 and finally grew to 27.12 TCF at the end of 2017 (Shetol MH et al., 2019).Worthwhile to mention that around 15.22 TCF gas has already been consumed.Moreover, it has been projected that the country would be able to fulfill the growing demand for natural gas for the next 10 to 12 years with the remaining 12 TCF gas reserves.Therefore, for Bangladesh, it is an urgent need to increase the amount of gas reserve.In the petroleum field, the reassessment of reservoir properties with advent techniques and methods is an integral part of the development of gas or oil fields.Several studies found that the reassessment of reservoir properties significantly increases the hydrocarbon reserve of the existing fields in the world as well as in Bangladesh (Shetol MH et al., 2019).This analysis is also a part of the reassessment of the hydrocarbon reservoir.

Table 2.The present status of 27 gas fields in Bangaldesh (Petrobangla, 2020).

This study targets the Srikail gas field in Bangladesh which was discovered in 1991-92 after an extensive twelvefold CDP seismic survey by Bangladesh Petroleum Exploration and Production Company Ltd.(BAPEX) in the Srikail area.The estimated gas reserve was 300 billion cubic feet (BCF) and thereby treated as a medium-sized gas field.The well-1 and well-2 at the Srikail gas field were drilled by the BAPEX in 2004 and 2007, respectively.To enhance the gas production from this field, later well-3 and well-4 weredrilled on the same closure (Hossain MIS et al., 2020).Currently, the daily gas production rate from two wells is around 41-44 million cubic feet and feeding to the national grid.However, for reserve growth study, the petrophysical properties reassessment of the reservoir is essential.This study thus aims to evaluate the reservoir properties again using the various geophysical well logs available for well-3.In this case, it is targeted to collect the log data for a small interval such as 0.1 m for each data.It is hoped that the findings of this study will provide new constraints of the petrophysical properties in the Srikail gas field which might be implemented for other gas fields in the reserve growth assessment.

2.Geological setting of the gas field area

The huge pile of sedimentary layers (around 20 km) in the Bengal Basin favors the accumulation of significant quantities of natural gas in Bangladesh.It is evident from the geological and geophysical explorations that Bangladesh has significant quantities of exploitable natural gas and coal resources.Bengal Basin is the result of very active tectonic activities.The continuous collision between the Indian plate and Eurasian plate results in the uplifting of the Himalayan orogeny in the north of Bengal Basin which contributing to the building up of a large landmass, the formation of the mega delta by the Ganges-Brahmaputra-Meghna major river system(Alam M et al., 2003; Curray JR, 1991).Additionally, the ongoing collision between the Indian and Burma plates in the east of the Bengal Basin forms series of structural elements favorable for the formation and accumulation of hydrocarbon.Such as the Morichakandi structure is situated in the westernmost part of the Chittagong-Tripura folded belt and is a symmetrical anticline with SE-NNE (Hossain AH, 1997).As the mega delta moves southwards accompanied by rapid subsidence of the basin, a huge thickness of deltaic to fluviodeltaic sediment was deposited and the eastern part has been uplifted into hilly landform incorporating itself into the frontal belt of the Indo-Burma Range (Alam M et al., 2003).Moreover, the Surma Basin, the eastern region of the country is the most prolific area to produce hydrocarbon (Imam B,2013).

Among 27 gas fields in Bangladesh, most of them are located within the Surma Basin (Fig.1; Imam B, 2013).The basin is located in the northeastern part of India.It forms a part of the Arakan-Assam Frontal Belt characterized by several N-S tending long narrow elongated anticlines and broad flat intervening synclines occurring in enechelon fashion (Hossain MIS et al., 2017).Among three geotectonic provinces in Bengal Basin, Sumra Basin is situated in the geotectonic province-2 (Hossain MIS et al., 2020).Besides,concerning hydrocarbon reservoir, there are three petroleum provinces in Bengal Basin (Imam B, 2013): The eastern folded belt, the central foredeep and the combined stable shelf and Hinge zone in the west-northwest, respectively (Fig.1;Imam B, 2013).The Surma Basin lies in the first province where the anticlinal structural folds form the hydrocarbon traps and is the most prolific gas province in Bangladesh.Towards the west, the slope of these structures reduces slowly and finally merges to the foredeep province-2, the modest prospect of petroleum.Conventionally, in Bengal Basin, the source-reservoir-trap-seal system depends on the tectonic characteristics, sedimentary environment and evolution of different parts of Bengal Basin (Imam B, 2013).Usually, the sandstone of the Miocene-Pliocene age is the dominant rock type for the hydrocarbon reservoir in Bangladesh whereas the hydrocarbon reserves have been demarcated in the depth between 1000 m and 3500 m ((Imam B, 2013; Hossain A et al., 1997).In our study gas field, the Srikail gas field belongs to geotectonic province-2 (Hossain MIS et al., 2020) as well as the petroleum province-2 (Imam B, 2013) and is situated within the Tripura Uplift, in the western part of the folded belt of the Bengal Foredeep.This gas field is surrounded by few anticlinal structures like Bakrabad to the south-west,Saldanadi to the east, Lalmai and Bangora to the south, and Titas to the north-east (Hossain MIS et al., 2020).Srikail gas reservoir consisted of multiple sandstone layers of Bhuban and Bokabil formations in the Miocene-Pliocene age.Three zones are well demarcated as the hydrocarbon-bearing zone for the well-3 in Srikail gas field.

3.Data and methods

3.1.Data availability and reading

Srikail gas field contains four (4) wells.Among these wells, in this study, the authors used the geophysical well logs data for well#3.Four suits of well logs data for this well were obtained from the BAPEX data centre that belongs to Bangladesh Oil, Gas and Mineral Corporation(PETROBANGLA) through proper authority.The suit of well logs consists of gamma ray log (GR), resistivity log (ILD),density log (RHOB) and neutron log (NPHI).The depth of the well#3 of the Srikail gas field is about 3350 m.Along with the wells, there are three hydrocarbon (gas) bearing zones.The depths ranging from 2615-2625 m, 2997-3031 m and 3170-3188 m are demarcated for zone-1, zone-2 and zone-3,respectively (Table 3).This study used the logs data for the three zones only due to official restrictions.While taking the log values in the case of all types of logs, first we slice the whole thickness into 0.1 m intervals for zone-1 and 0.2 m intervals for zone-2 and zone-3, respectively.After that, the reading was taken from each interval.

Table 3.The depth ranges and the corresponding thickness of varies zones along well#3.

Therefore, the total number of readings for zone-1, zone-2 and zone-3 are 101, 171 and 91, respectively.Later the average value for each log and zone was used to estimate the petrophysical properties of the zones applying the proper methods and equations.Besides the log data, some associated necessary data like surface temperature, total well depth,bottom-hole temperature, formation matrix density, formation fluid density were also collected from the data center.Worthwhile to mention that as per the agreement with the authority of the data center, all the reading was taken insidetheir office and was not permitted to take the log sheets at any form outside the office.Therefore, in this paper, there is no figure for original logs (log motifs).Digitization of well logs data was carried out by MS-Excel software manually.

Fig.1.Location map of the 27 gas fields (number followed the Table 1) with regional tectonic settings (map revised from Shetol MH et al.,2019).

3.2.Methods

The conventional methods were used in this analysis for the assessment of the petrophysical properties of the reservoir.Petrophysical properties such as hydrocarbon saturation (Sh),porosity (Φ), permeability (K), water saturation (Sw), water resistivity (Rw), etc were evaluated and analyzed according to the following discussion.

3.2.1.Shale volume assessmentIn the reservoir, the shale is a heterogeneous sedimentary rock containing variable content of clay minerals (illite,kaolinite, chlorite and montmorillonite) and organic matter(Brock J, 1986; Mehana M and El-monier I, 2016).It was found that the shale present in the reservoir formation has severe effects on reservoir petrophysical properties and thereby reduces the effectiveness and total porosity and permeability of the reservoir (Kamel MH and Mohamed MM,2006; Ruhovets N and Fertl WH, 1982).Moreover, the uncertainties in formation evaluation and proper estimation of oil and gas reserves may be arisen by the existence of shale(Abudeifa AM et al., 2016).Therefore, the proper determination of the amount of shale volume in the reservoir is very important in reservoir characterization.In this study,we utilized the following steps for shale volume estimation.The first step was to estimate the shale volume with the help of a gamma-ray log (GR) using the Schlumberger formula.It was used to evaluate the shale distribution of a reservoir(Whitehurst C, 2014):

Where,

Vsh=shale volume, GRlog= Gamma-ray reading of formation which varies with depth, GRmin= Minimum gamma-ray (clean sand or carbonate), GRmax= Maximum gamma-ray (shale)

To obtain the more accurate result of the shale volume, the estimated value was then re-estimated using the following Schlumberger-clavier equation (Clavier C et al., 1971).

3.2.2.Porosity determinationPorosity, one of the most influential parameters in the petrophysical and volumetric estimation and the majority of the reservoirs’ characteristics cannot be expressed completely without the usage and calculation of porosity (Abraham-A RM and Taioli F, 2017).For the explanation of reservoirs'attributes such as grain sizes and sorting, shale content,cementation, consolidation of rocks, pore sizes and interconnectivity among others, the relationship between porosity and reservoir's flow units is very effective(Schlumberger Limited, 1991; Asquith G and Krygowski D,2004; Tiab D and Donaldson EC, 2012).Therefore, the reservoir properties such as free fluid index (FFI),permeability (K), reservoir quality index (RQI) and flow zone indicator (FZI) are directly or indirectly dependent upon the porosity and one another.In this study, we estimated the porosity from the combination of density and neutron logs.The formula for determining the porosity from the density log is as follows (Rider MH, 1966):

Where,

ϕd= density porosity,ρma= matrix density (Sandstone =2.644 g/cm3),ρb= formation bulk density, the log reading,varies with depth, ρf= fluid density (Fresh water=1 g/cm3).

The porosity was measured by neutron log through the following equation, the clay corrected neutron porosity (Ross Crain ER, 1999):

Where,

ϕn-corr= The neutron porosity, NPHI = Neutron log value of zone of interest, NPHIsh= Average neutron value of shale volume.

To obtain the more accurate porosities from densityneutron logs the following equation was used when the two logs recorded different porosities for a zone (Whitehurst C,2016):

Where,

Φ= The percent of porosity,ϕn= Neutron porosity andϕd=Density porosity

3.2.3.Water saturation calculationWater saturation is an important parameter used in reservoir characterization such as the modeling for reserve estimation because it gives an idea of the percentage of the pore spaces occupied by water and oil or gas and hence the total amount of hydrocarbon present in the pore spaces of the reservoir (Sam-Marcus J et al., 2018).The water saturation of any formation is directly related to the formation’s porosity.The porosity obtained in this study has been corrected in terms of shale.Usually, the type of water saturation depends on the nature of pore space.It is termed as total water saturation in case of total porosity and effective water saturation when the pore space is considered as effective porosity (Islam GA et al., 2017).However, in this analysis,deploying the Schlumberger Offshore Services (1975) water saturation equation, the water saturation for both of the three zones was calculated as:

Where,

Sw= Water saturation,Rt= True resistivity of formation,Vsh= Shale volume,Rsh= Resistivity of a nearby pure shale,Rw= Formation water resistivity andΦ= Average porosity.

Table 4 illustrates the relevant parameters and corresponding values used in water saturation calculation.

Table 4.Parameters and corresponding values used for water saturation estimation.

3.2.4.Hydrocarbon saturation calculationHydrocarbon saturation, the most important properties of the reservoirs used for the calculation of the total reserve of hydrocarbon.Conventionally, hydrocarbon saturation depends on water saturation and is the part of pore volume in aformation occupied by gas (Rider MH, 1966).Besides, when the permeable zone shows more than 60% hydrocarbon saturation (Sh) value then it is commonly treated as a hydrocarbon-bearing zone (Krygowski GAD, 2006).The estimation of hydrocarbon saturation is very easy when the formation water saturation is obtained.The process is just to subtract the water saturation from the 100 percent saturation of the formation as equation 7:

Where,

Sh= Hydrocarbon saturation (%),Sw= water saturation(%)

3.2.5.Permeability calculationPermeability is one of the properties that govern the productivity of the reservoirs.In most cases, it is the most difficult property to determine and predict.Some factors like pore size and pore-throat geometry, as well as the porosity, on which permeability is dependent.Timur equation relates permeability to irreducible Swand porosity, after taking some of these factors into account and therefore can be applied only in hydrocarbon-bearing zones (Equation 8).The following equation of Watts M (2013) can be effectively used to estimate the absolute permeability of the reservoir for a medium-gravity hydrocarbon zone.

Where,

K= absolute permeability in mD,ϕe= effective porosity as a volume fraction, andSwirr= effective water saturation above the transition zone as a fraction of pore volume.

In this study, the above-mentioned equation of Watts M(2013) was used to determine the permeability of the three zones.In hydrocarbon zones, where irreducible water saturation is taken equal to water saturation (Sw) values from any shale-corrected method (Singh N, 2019).

4.Results

In this analysis, the multiple geophysical well logs data such as gamma-ray logs, resistivity logs, sonic logs, and neutron logs were taken from 0.1 m interval and 0.2 m interval for zone-1 and both zone-2 and zone-3, respectively.The result of petrophysical parameters such as shale volume,porosity, water saturation and hydrocarbon saturation were discussed individually in the following sections.At first, the findings were illustrated for each zone and later the average value for the three zones.

4.1.Assessment of shale volume

The gamma-ray log was used to calculate the volume of shale in porous reservoirs.The result showed that the initial average shale volume is 33.97%, 71.08% and 69.15% for zone-1, zone-2 and zone-3, respectively.The corrected average shale volume for zone-1, zone-2 and zone-3is 21.07%.53.67% and 51.71%, respectively.Since the value for zone-1 is much lower than the others, it reveals that zone-1 is mostly sandy.The summary of estimated shale volume in different zones is shown in Table 5.

4.2.Porosity determination

Porosity determination is very important for determining fluid saturation in the reservoir.In this study, the effective porosity was determined from the combination of total porosity and shale volume using a conventional equation.First, we calculated the porosity separately from density logs and neutron logs (Table 6).After that, the average porosity was determined.The obtained average porosity was 33.89%,29.83% and 28.76% for zone-1, zone-2 and zone-3,respectively (Table 6).The overall average porosity for all zones is 31.49%.

4.3.Water saturation calculation

Water saturation plays a vital role in estimating reservoir characteristics.Water saturation was calculated using both of the Indonesian water saturation equations by Poupon A and Leveaux J (1971) and Schlumberger Offshore Services (1975)water saturation equation.It was observed that the Schlumberger Offshore Services (1975) water saturation equation gives better results in our case.Hereby the result from Schlumberger Offshore Services (1975) was consideredin this analysis.The obtained water saturation values for zone-, zone-2 and zone-3 are 68.46%, 83.17% and 76.61%,respectively.The average value is 23.92% (Table 7).For estimation of the average value for each zone, all estimated values of water saturation at each 0.1 m interval (for example 100 values for zone 1: 2615-2625 m) were averaged arithmetically.

Table 5.Average shale volume of study zones of Well#3 of Srikail gas field.

Table 6.The obtained porosity values for different zones.

4.4.Hydrocarbon saturation calculation

Hydrocarbon saturation depends on water saturation.It was calculated from the alteration of water saturation by the deduction of water saturation value (%) from 100.The results of the hydrocarbon (gas) saturation of the study zones are presented in Table 8.Results showed that the average hydrocarbon saturation value for zone-1, zone-2 and zone-3 is of 68.46%, 83.17% and 76.61%, respectively.The overall average value is 76.08%.

Table 7.Average water saturation of study zones.

Table 8.Average hydrocarbon (gas) saturation of study zones.

5.Discussion

Along with the well#3 at Srikail Gas field, three potential hydrocarbon (gas) producing zones at various depths areavailable.Zone-2 having a much higher thickness (34 m)rather than the others (Fig.2a).This zone-2 belongs to the depth range from 2997 m to 3031 m.Besides, zone-1 and zone-3 have also reasonable thicknesses such as 10 m and 18 m, respectively.We read the log values at every 0.1 m for zone-1 and every 0.2 m for zone-2 and zone-3 to get better constraints of the gas field.

The volume of shale is used to characterize the shale distribution of a reservoir.Shale volume greatly affects the water saturation and consequently, the hydrocarbon contains.Generally lower shale volume indicates better reservoir conditions.The estimated average shale volume of 21.07% at zone-1 indicates that the sand governing reservoir with a very little amount of shale.Again, the average shale volume of zone-2 and zone-3 were identified as 53.67% and 51.71%respectively indicating that shaly sand governing lithology(Fig.2b).Hence zone-1 indicates better reservoir conditions than the other two zones.

Basically, the porosity data are routinely used to assess and estimate the potential hydrocarbon contained in the reservoir.The average porosity of zone-1 was 35.89% which indicating the excellent porosity of this prospective hydrocarbon-bearing zone.Further, the average porosity for zone-2 and zone-3 was 29.83% and 28.76% indicating very good quality porosity of these prospective hydrocarbonbearing zones (Fig.2c).

From the alteration of water saturation, the obtained hydrocarbon saturation values indicate that the reservoir is productive because all of the values exceeded 60 % in this study.Zone -2 has the highest hydrocarbon saturation value(83.17%) (Fig.2d).So, it can be said that the reservoir was formed in the high accumulation of hydrocarbon and it is commercially productive.

Based on the estimated overall petrophysical properties, it can be summarized that the Srikail Gas field is productive in terms of hydrocarbon.As it was mentioned earlier that theconcept of this research work was that retrieving or reading the log data from smaller intervals may produce more accurate values of the petrophysical properties.Therefore, to justify the result of this study, we made a comparison of this result with the available results determined previously at the same gas field (Hossain MIS et al., 2020).For example,Hossain MIS et al.(2020) found the range of hydrocarbon saturation from 53.1% to 75.1% whereas our result shows it is about 76.1%.Similarly, some other parameters also showing higher values than previously.

Fig.2.a-Thickness of HC zones; b-comparison of average shale volume of zones 1, 2 and 3; c-comparison of average porosity of zones 1, 2 and 3; d-comparison of average water saturation of of zones 1, 2 and 3; e-comparison of average hydrocarbon saturation of zones 1, 2 and 3;f-comparison of petrophysical parameters of of zones 1, 2 and 3.

6.Conclusion

Srikail gas field is located in a petroleum prolific sedimentary basin in Bangladesh.Currently, 4 wells are present in this field.Well#3 is considered in this study.The gas fields contain three gas-bearing zones observed along with the well.The quantitative analysis of petrophysical parameters was used to characterize the gas reservoir properties by using geophysical well logs such as gamma ray log, resistivity log, neutron logr and density log and some accessory data.In evaluating the various petrophysical properties of the reservoir, the measurements of log data were read for every 0.1 m interval and 0.2 m intervals.The conventional methods of calculation were applied in this study.The average shale volume for zone-1, zone-2 and zone-3 was 21.07%, 53.67% and 51.71%, respectively which revealed that zone-1 indicates better reservoir condition than the other two study zones.The average porosity for zone-1 was 35.89% indicating excellent porosity and for zone-2 and zone-3 were 29.83% and 28.76%, respectively indicating very good quality porosity of these prospective hydrocarbonbearing zones.The average water saturation in zone-1, zone-2 and zone-3 were 31.54%, 16.83% and 23.39%, respectively and from the alteration of water saturation, the obtained average hydrocarbon saturations were 68.46%, 83.17% and 76.61% respectively.So, all the calculated values of hydrocarbon saturation were more than 60% revealed these zones as hydrocarbon-bearing zones.From the overall point of view, zone-2 is the most productive zones among the three zones of well#3.In comparison with previous studies, it is found that the estimated values of each parameter are a bit higher than in previous studies.Therefore, this study concludes that data retrieving at small intervals provide better results rather than large interval data reading.A similar kind of study can be thus implemented for other wells of this gas field as well as for other gas fields in Bangladesh.

CRediT authorship contribution statement

Md.Shahadot Hossain and M.Moklesur Rahman conceived of the presented idea.Most.Habiba Khatun and Md.Rubel Haque read and analyse the log data with the support of Md.Shahadot Hossain.Moreover, Md.Shahadot Hossain and M.Moklesur Rahman write the manuscript.

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgement

The authors are very much grateful to the Authority of BAPEX data Centre and Bangladesh Oil, Gas and Mineral Corporation (PETROBANGLA) for providing the log data.The authors are thankful to the K.C.Wong Education Foundation (GJTD-2019-04) and the Chinese Academy of Sciences as President’s International Fellowship Initiative(PIFI) for a Postdoctoral fellow to M.Moklesur Rahman(2019PE0025).Moreover, the authors especially thank the Chairman of the Department of Petroleum and Mining Engineering, Jessore University of Science and Technology for giving support to this research work.