scholarly journals Petrophysical analysis of “explorer” wells using well log and core data(a case study of “explorer” field, offshore Niger Delta, Nigeria)

2020 ◽  
Vol 8 (2) ◽  
pp. 219
Author(s):  
Abe J. Sunday ◽  
Lurogho S. Ayoleyi
Keyword(s):  
Linear Relationship ◽  
Correlation Coefficient ◽  
Niger Delta ◽  
Gamma Ray ◽  
Regression Equation ◽  
Well Log ◽  
Data Set ◽  
Core Data ◽  
Density Values ◽  
Strong Linear Relationship

Reservoir characterization involves computing various petrophysical parameters and defining them in terms of their quantity and quality so as to ascertain the yield of the reservoir. Petrophysical well log and core data were integrated to analyze the reservoir characteristics of Explorer field, Offshore, Niger Delta using three wells. The study entails determination of the lithology, shale volume (Vsh), porosity (Φ), permeability (K), fluid saturation and cross plotting of petrophysical and core values at specific intervals to know their level of correlation. The analysis identified twelve hydrocarbon-bearing reservoir from three different wells. Average permeability value of the reservoir is 20, 0140md while porosity value range between 18% to 39%. Fluid type defined in the reservoirs on the basis of neutron/density log signature were basically water, oil and gas, low water saturation values ranging from 2.9% to 46% in Explorer wells indicate high hydrocarbon saturation. The Pearson Correlation Coefficient and Regression Equation gave a significant relationship between petrophysical derived data and core data. Scatter plot of petrophysical gamma ray values versus core gamma ray values gave an approximate linear relationship with correlation coefficient values of 0.6642, 0.9831 and 0.3261. Crossplot of petrophysical density values and core density values revealed that there is a strong linear relationship between the two data set with correlation coefficient values of 0.7581, 0.9872 and 0.3557, and the regression equation confirmed the relationship between the two data set. Also the scatter plot of petrophysical porosity density values versus core porosity density values revealed a strong linear relationship between the two data set with correlation coefficient values of 0.7608 and 0.9849, the regression equation confirmed this also. Crossplot of petrophysical porosity density values versus core porosity density values in Well 3 gave a very weak correlation coefficient values of 0.3261 and 0.3557 with a negative slope. The petrophysical properties of the reservoirs in Explorer Well showed that they contain hydrocarbon in commercial quantity and the cross plot of the petrophysical and core values showed direct relationship in most of the wells.  

scholarly journals Sedimentology and ichnology of Neogene Coastal Swamp deposits in the Niger Delta Basin, Nigeria

Geologos ◽  
2016 ◽  
Vol 22 (3) ◽  
pp. 191-200 ◽  
Author(s):  
Sunny C. Ezeh ◽  
Wilfred A. Mode ◽  
Berti M. Ozumba ◽  
Nura A. Yelwa
Keyword(s):  
Niger Delta ◽  
Depositional Environment ◽  
Gamma Ray ◽  
Depositional Environments ◽  
Well Log ◽  
Data Set ◽  
Depositional Settings ◽  
Niger Delta Basin ◽  
Core Descriptions ◽  
Tidal Processes

Abstract Often analyses of depositional environments from sparse data result in poor interpretation, especially in multipartite depositional settings such as the Niger Delta. For instance, differentiating channel sandstones, heteroliths and mudstones within proximal environments from those of distal facies is difficult if interpretations rely solely on well log signatures. Therefore, in order to achieve an effective and efficient interpretation of the depositional conditions of a given unit, integrated tools must be applied such as matching core descriptions with wireline log signature. In the present paper cores of three wells from the Coastal Swamp depositional belt of the Niger Delta are examined in order to achieve full understanding of the depositional environments. The well sections comprise cross-bedded sandstones, heteroliths (coastal and lower shoreface) and mudstones that were laid down in wave, river and tidal processes. Interpretations were made from each data set comprising gamma ray logs, described sedimentological cores showing sedimentary features and ichnological characteristics; these were integrated to define the depositional settings. Some portions from one of the well sections reveal a blocky gamma ray well log signature instead of a coarsening-upward trend that characterises a shoreface setting while in other wells the signatures for heteroliths at some sections are bell blocky in shaped rather than serrated. Besides, heteroliths and mudstones within the proximal facies and those of distal facies were difficult to distinguish solely on well log signatures. However, interpretation based on sedimentology and ichnology of cores from these facies was used to correct these inconsistencies. It follows that depositional environment interpretation (especially in multifarious depositional environments such as the Niger Delta) should ideally be made together with other raw data for accuracy and those based solely on well log signatures should be treated with caution.

Missing well log prediction using convolutional long short-term memory network

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. WA159-WA171 ◽  
Author(s):  
Nam Pham ◽  
Xinming Wu ◽  
Ehsan Zabihi Naeini
Keyword(s):  
Continental Shelf ◽  
Gamma Ray ◽  
Short Term Memory ◽  
Rock Physics ◽  
Rock Properties ◽  
Well Log ◽  
Short Term ◽  
Data Set ◽  
Term Memory ◽  
Long Short Term Memory

Reservoir characterization involves integration of different types of data to understand the subsurface rock properties. To incorporate multiple well log types into reservoir studies, estimating missing logs is an essential step. We have developed a method to estimate missing well logs by using a bidirectional convolutional long short-term memory (bidirectional ConvLSTM) cascaded with fully connected neural networks. We train the model on 177 wells from mature areas of the UK continental shelf (UKCS). We test the trained model on one blind well from UKCS, three wells from the Volve field in the Norwegian continental shelf, one well from the Penobscot field in the Scotian shelf offshore Canada, and one well from the Teapot Dome data set in Wyoming. The method takes into account the depth trend and the local shape of logs by using ConvLSTM architecture. The method is examined on sonic log prediction and can produce an accurate prediction of sonic logs from gamma-ray, density, and neutron porosity logs. The advantages of our method are that it is not applied on an interval by interval basis like rock-physics-based methods and it also outputs the uncertainties facilitated by dropout layers and Monte Carlo sampling at inference time.

scholarly journals Shale volume and porosity delineation of coast swamp depobelt in Niger delta region, Nigeria, using well log

2019 ◽  
Vol 7 (2) ◽  
pp. 142
Author(s):  
Ubong Essien
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Water Saturation ◽  
Effective Porosity ◽  
Neutron Density ◽  
Well Log ◽  
Shale Formations ◽  
Log Data ◽  
Shale Volume ◽  
Niger Delta Region

Well log data from two wells were evaluated for shale volume, total and effective porosity. Well log data were obtained from gamma ray, neutron-density log, resistivity, sonic and caliper log respectively. This study aimed at evaluating the effect of shale volume, total and effective porosity form two well log data. The results of the analysis depict the presence of sand, sand-shale and shale formations. Hydrocarbon accumulation were found to be high in sand, fair in sand-shale and low in shale, since existence of shale reduces total and effective porosity and water saturation of the reservoir. The thickness of the reservoir ranged from 66 – 248.5ft. The average values of volume of shale, total and effective porosity values ranged from 0.004 – 0.299dec, 0.178 – 0.207dec and 0.154 – 0.194dec. Similarly, the water saturation and permeability ranged from 0.277 – 0.447dec and 36.637 - 7808.519md respectively. These values of total and effective porosity are high in sand, fair in sand-shale and low in shale formations. The results for this study demonstrate: accuracy, applicability of these approaches and enhance the proper evaluation of petrophysical parameters from well log data.    

scholarly journals DELINEATION OF HYDROCARBON SATURATED RESERVOIR SAND USING INTEGRATED 3D PRE-STACK SEISMIC AND WELL LOG DATA IN BONGA – FIELD, CENTRAL SWAMP DEPOBELT, ONSHORE NIGER DELTA, NIGERIA

2020 ◽  
Vol 5 (2) ◽  
pp. 64-68
Author(s):  
Innocent Kiani ◽  
Aniefiok Sylvester Akpan
Keyword(s):  
Cross Sections ◽  
Niger Delta ◽  
Gamma Ray ◽  
Water Saturation ◽  
Seismic Inversion ◽  
High Resistivity ◽  
Well Log ◽  
Fluid Properties ◽  
Exploratory Wells ◽  
Depth Ranges

This study has successfully delineated the lateral continuity of hydrocarbon saturated sand reservoir in Bonga field, Niger Delta. 3D pre-stack seismic volume and well logs from two (2) exploratory wells were employed in the pre-stack seismic inversion analysis. The delineated BGA reservoir sand spans across the two (2) wells labelled Bonga-26 and Bonga-30. The reservoir depth ranges from 10490 ft to 10620 ft in Bonga-26 while the reservoir depth ranges from 10390 ft to 10490 ft in Bonga-30. The delineated reservoir is characterized by low gamma ray (< 75 API), water saturation, shale volume and high resistivity as deciphered in their respective well log curves signature. Rock attribute crossplot was carried out to discriminate between the formation fluid and lithology. The crossplot space of VP-VS ratio versus acoustic impedance (AI), discriminates the formation properties into lithology and fluid (gas and brine sand) based on clusters inferring the presence of each formation fluid properties. The inversion cross sections of P-impedance, S-impedance, density (ρ) and VP-VS ratio depicts the spread and lateral continuity of the reservoir sand across the well locations. The delineated zones reveal low P-impedance, density, VP-VS ratio and slight increase in S-impedance which further validate the presence of hydrocarbon in the field.

scholarly journals THE EFFECT OF DENSITY-VELOCITY RELATION PARAMETERS ON DENSITY CURVES IN TAU (τ) FIELD, NIGER DELTA BASIN

2020 ◽  
Vol 4 (2) ◽  
pp. 54-58
Author(s):  
Atat, J. G. ◽  
Akankpo, A. O. ◽  
Umoren, E. B. ◽  
Horsfall, O. I. ◽  
Ekpo, S. S
Keyword(s):  
Density Estimation ◽  
Niger Delta ◽  
Accurate Result ◽  
Oil Field ◽  
Well Log ◽  
Velocity Relation ◽  
Density Values ◽  
Niger Delta Basin

We considered the constants obtained for tau (𝜏)Field in the Niger Delta basin from well-log data of three wells (A,B,C) to investigate the effect of inclusion of these constants on density-velocity relation using Hampson Russell Software to generate density curve in tau field. The curves were compared to those generated from Gardner and Lindseth constants and in-situ density curves. Many researchers have worked on constants for density-velocity equations for different Fields; their results always differ from Gardner and Lindseth constants including the constants of Atat et al., 2020 which are considered in this investigation as Tau Field local fit constants. Our findings support the results of these researchers. Results indicate over estimation of density curves when using Gardner and Lindseth constants. The challenge is that in-situ density curves are not accurate due to sand-shale overlap of density values. The most improved and accurate result is given by the density curves obtained using the constants for specific sand and shale lithologies (local fits). This verifies the need for the determination of constants for local fit of the oil field under investigation. The pink curves truly indicate the density estimation for the tau field which is very reliable in the characterisation of reservoir.

scholarly journals Seismo-Structural Interpretation and Petrophysical Evaluation of Ugwu-Field, Coastal Swamp Depositional Belt of the Niger Delta Basin

2020 ◽  
Vol 24 (9) ◽  
pp. 1583-1591
Author(s):  
E.B. Ugwu ◽  
S.A. Ugwu ◽  
C.U. Ugwueze ◽  
S.U. Eze ◽  
M.A. Bello
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Hanging Wall ◽  
High Amplitude ◽  
Seismic Facies ◽  
Well Log ◽  
Structural Interpretation ◽  
Petrophysical Parameters ◽  
North East ◽  
Petrophysical Evaluation

Structural interpretation of 3-D seismic data and well log have been applied to unravel hydrocarbon entrapment pattern and petrophysical  parameters of X-field within the coastal swamp region of the Niger Delta.. Four reservoir intervals (A, B, C and D) delineated as (W-026, 032, 042 and 048) using gamma ray and resistivity log response. Structural interpretation for inline 5158 revealed four horizons (A, B, C and D) and eight (8) faults labelled (F1, F2, F12, F13, F21, F22, F23, and F24) were mapped. It was observed that the hanging wall block due to reverse drag or rollover anticline slided over fault F12 and created fault F2, thereby creating subsidence where sediments can be deposited. Therefore, faults F2 and F12 created rollover structures which cuts across the entire four reservoirs and invaluably responsible for trapping of hydrocarbon in the field. RMS map developed for horizons ‘A’ and ‘B’ revealed high amplitude anomalies, while variance attribute for both horizons showed relatively uniform lithology observed from east to west across the study area. While from north-east to south west, variance was observed to increase relatively which indicates different lithology. These trend exposes dipping of the channel fill at both flanks by creating extensive faulting. Results of petrophysical evaluation for reservoirs ‘A’ and ‘B’ across the four wells were analyzed. For reservoir ‘A’, porosity values of 32.8%, 24.8%, 25.9% and 27.1% were obtained for wells W-048, 042, 026 and 032 respectively with an average of 27.65%, while for reservoir ‘B’ porosity values of 26.83%, 26.93%, 25.59% and 27.99% for wells W-048, 042, 026 and 032 were obtained respectively with an average of 26.84%. This porosity values were rated very good to excellent for reservoir ‘A’ and very good for reservoir ‘B’, while Permeability values of the order (K > 1000mD) were obtained for both reservoirs across the four wells and is rated excellent. Hydrocarbon saturation (Shc) across the four wells averages at 68.57% for reservoir ‘A’ and 68.67% for reservoir ‘B’ which is high. Log motifs using gamma ray log for well-026 was integrated with seismic facies to infer on depositional environment of the reservoirs horizons showed a combination of serrated funnel/blocky shape log response and coarsening upward cycles. For reservoirs ‘A’, ‘B’ and ‘C’ the log shape pattern indicates deposition in a fluvial / tidal, channel environment while for reservoir ‘D’ the pattern indicates deposition in deltaic front environment. Isochore maps computed for horizons ‘A’ and ‘B’, shows that horizon ‘A’ is relatively thick and this pattern suggests increased tectonic activities during deposition of reservoir ‘A’ and is an indication that reservoir ‘A’ is a synrift deposit. Keywords: 3-D Seismic interpretation, Faults, Seismostratigraphy, Well log, Seismic Attributes, Petrophysical parameters

Determination of Chitosan Oligosaccharide Content by Acetylacetone Spectrophotometry Method

2012 ◽  
Vol 503-504 ◽  
pp. 543-547 ◽  
Author(s):  
Ze Ping Xu ◽  
Chuan Lun Yang ◽  
Xin Qing Zhang ◽  
Xiu Zhi Wang ◽  
Bao Sheng Huang
Keyword(s):  
Hydrochloric Acid ◽  
Linear Relationship ◽  
Regression Equation ◽  
Common Method ◽  
Chitosan Oligosaccharide ◽  
Average Recovery ◽  
Good Linear ◽  
Good Linear Relationship

Objective: To establish a common method to detect the content of chitosan oligosaccharide. Methods: Chitosan oligosaccharide was hydrolyzed completely by concentrated hydrochloric acid, and the solution was regulated into neutral with NaOH. Then, determined the absorbance in 525nm, and substituted into the regression equation to determine the results. Results: The results showed there was a good linear relationship when the concentration of chitosan oligosaccharide ranged from 0.02 mg/mL to 0.12 mg/mL, r2 = 0.999. The average recovery of chitosan oligosaccharide samples was 99.25%. Conclusion: The method is sensitive, accurate and simple. It is applied to determine of the content of chitosan oligosaccharide.

scholarly journals Sacral incidence to pubis: a novel and alternative morphologic radiological parameter to pelvic incidence in assessing spinopelvic sagittal alignment

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yasuhito Takahashi ◽  
Kei Watanabe ◽  
Masashi Okamoto ◽  
Shun Hatsushikano ◽  
Kazuhiro Hasegawa ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Pelvic Incidence ◽  
Sagittal Alignment ◽  
Intraclass Correlation ◽  
Hip Dislocation ◽  
Standing Position ◽  
Regression Equation ◽  
Whole Body ◽  
Spinopelvic Parameters ◽  
Pelvic Inclination

Abstract Background Although pelvic incidence (PI) is a key morphologic parameter in assessing spinopelvic sagittal alignment, accurate measurements of PI become difficult in patients with severe hip dislocation or femoral head deformities. This study aimed to investigate the reliability of our novel morphologic parameters and the correlations with established sagittal spinopelvic parameters. Methods One hundred healthy volunteers (25 male and 75 female), with an average age of 38.9 years, were analysed. Whole-body alignment in the standing position was measured using a slot-scanning X-ray imager. We measured the established spinopelvic sagittal parameters and a novel parameter: the sacral incidence to pubis (SIP). The correlation coefficient of each parameter, regression equation of PI using SIP, and regression equation of lumbar lordosis (LL) using PI or SIP were obtained. The intraclass correlation coefficient (ICC) was calculated as an evaluation of the measurement reliability. Results Reliability analysis showed high intra- and inter-rater agreements in all the spinopelvic parameters, with ICCs > 0.9. The SIP and pelvic inclination angle (PIA) demonstrated strong correlation with PI (R = 0.96) and pelvic tilt (PT) (R = 0.92). PI could be predicted according to the regression equation: PI = − 9.92 + 0.905 * SIP (R = 0.9596, p < 0.0001). The ideal LL could be predicted using the following equation using PI and age: ideal LL = 32.33 + 0.623 * PI – 0.280 * age (R = 0.6033, p < 0.001) and using SIP and age: ideal LL = 24.29 + 0.609 * SIP – 0.309 * age (R = 0.6177, p < 0.001). Conclusions Both SIP and PIA were reliable parameters for determining the morphology and orientation of the pelvis, respectively. Ideal LL was accurately predicted using the SIP with equal accuracy as the PI. Our findings will assist clinicians in the assessment of spinopelvic sagittal alignment. Trial registration This study was retrospectively registered with the UMIN Clinical Trials Registry (UMIN000042979; January 13, 2021).

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