scholarly journals Geothermal modelling and its application to hydrocarbon generation from agbada formation. a case study of USANi field, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 75
Author(s):  
Godwin Aigbadon ◽  
Anthony Okoro ◽  
Elesius Akpunonu ◽  
Rosemary Nimnu ◽  
Azuka Ocheli
Keyword(s):  
Gamma Ray ◽  
Geothermal Gradient ◽  
Hydrocarbon Generation ◽  
Sonic Log ◽  
Resistivity Logs ◽  
Source Rock Evaluation ◽  
Geothermal Model ◽  
Niger Delta Basin ◽  
Gamma Ray Log

The geothermal model was done with the integration of surface. Subsurface temperature's data and formation depth values from suites of well log in the study field. The well comprises Gamma-ray log (GR log), Spontaneous Potential logs (SP log), Resistivity logs, Formationdensity, Neutron log and Sonic log. The suites of welllog within the studied sequences penetrates Agbada and the Benin Formation. The Benin Formation comprises mainly of continental sands, and the Agbada Formation consist of alternating sequence of sand and shales within the study wells. The estimated thickness and temperature values within the study field falls within the range from 1357- 3500m and 101 O C – 120.5 O C with estimated geothermal gradient range of (0.028 - 0.03 O C/100m) in the field. The geo-temperatures results range of 101.60 O C – 119.60 OCat modeled depth of 1357m- 3500m, indicating that the shale sequence at the basal path of the Agbada Formation is thermally matured with sufficient organic matter to generate hydrocarbon in the study field as earlier believe to be immature and cannot generate hydrocarbon. The geothermal model can be applicable to any sedimentary basin in the world. This work is also an important tool in source rock evaluation to compliment petroleum geochemistry and position the hydrocarbon generating window of the study field.

Electrofacies in gas shale from well log data via cluster analysis: A case study of the Perth Basin, Western Australia

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Amir Torghabeh ◽  
Reza Rezaee ◽  
Reza Moussavi-Harami ◽  
Biswajeet Pradhan ◽  
Mohammad Kamali ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Gamma Ray ◽  
Cost Effective ◽  
Gas Production ◽  
Sonic Log ◽  
Cost Effective Method ◽  
Distance Data ◽  
Resistivity Log ◽  
Gamma Ray Log

AbstractIdentifying reservoir electrofacies has an important role in determining hydrocarbon bearing intervals. In this study, electrofacies of the Kockatea Formation in the Perth Basin were determined via cluster analysis. In this method, distance data were initially calculated and then connected spatially by using a linkage function. The dendrogram function was used to extract the cluster tree for formations over the study area. Input logs were sonic log (DT), gamma ray log (GR), resistivity log (IND), and spontaneous potential (SP). A total of 30 reservoir electrofacies were identified within this formation. Integrated geochemical and petrophysics data showed that zones with electrofacies 3, 4, 9, and 10 have potential for shale gas production. In addition, the results showed that cluster analysis is a precise, rapid, and cost-effective method for zoning reservoirs and determining electrofacies in hydrocarbon reservoirs.

Seismic characterization and origin of clinoforms in lacustrine depositional environments: a case study from the Cretaceous of the South Atlantic

2020 ◽  
pp. SP509-2019-148
Author(s):  
Andrew J. Barnett ◽  
Lucy Fu ◽  
Tolu Rapasi ◽  
Cinzia Scotellaro ◽  
Jaydip Guha ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Lower Energy ◽  
Gamma Ray ◽  
Depositional Environments ◽  
Longshore Sediment Transport ◽  
Seismic Characterization ◽  
Bona Fide ◽  
Flooding Events ◽  
Gamma Ray Log

AbstractThe lacustrine Itapema Formation in the Santos Basin locally comprises 102 m thick clinoforms identified seismically and corroborated by several well penetrations. Individual clinoforms, as proven by well penetrations, are composed of 102 m thick successions of basinward-dipping molluscan grainstones and rudstones. Manual dip picking of borehole images shows upward-increasing dips consistent with seismic geometries and a predominance of longshore sediment transport. Clinoforms are bound at their top and base by strata with significantly lower dips recognizable on both seismic and borehole images. Elevated gamma-ray log responses together with sidewall core samples indicate that these intervals correspond to more argillaceous facies which are interpreted as lake flooding events. While the existence of bona fide clinoforms is demonstrated by a range of subsurface data, their precise origin remains enigmatic. The majority of the bivalve genera that make up the grain-supported carbonates appear to be infaunal or semi-infaunal. As such the clinoforms represent large bars produced through the re-working of bivalves from lower-energy depositional environments by shore-parallel currents.

scholarly journals Depositional Environment and facies analysis of Useni- 1, Niger Delta Basin, using well logs, core data

2019 ◽  
Vol 7 (1) ◽  
pp. 58
Author(s):  
G. O. Aigbadon ◽  
E. O. Akpunonu ◽  
S. O. Agunloye ◽  
A. Ocheli ◽  
O. O .Akakaru
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Oil Field ◽  
Well Logs ◽  
Depth Range ◽  
Depositional Facies ◽  
Core Data ◽  
Delta Plain ◽  
Niger Delta Basin ◽  
Gamma Ray Log

This study was carried out integrating well logs and core to build reservoir model for the Useni-1 oil field. Core data and well logs were used to evaluate the petrophysical characteristics of the reservoirs. The paleodepositional environment was deduce from the wells and cores data. The depositional facies model showed highly permeable channels where the wells where positioned. The environments identified that the fluvial channel facies with highly permeable zones constituted the reservoirs. Four reservoirs were mapped at depth range of 8000ft to 8400ft with thicknesses varying from 20ft to 400ft. Petrophysical results showed that porosity of the reservoirs varied from 12% to 28 %; permeability from 145.70 md to 454.70md; water saturation from 21.65% to 54.50% and hydrocarbon saturation from 45.50% to 78.50 %. Core data and the gamma ray log trends with right boxcar trend indicate fluvial point bar and tidal channel fills in the lower delta plain setting. By-passed hydrocarbons were identified in low resistivity pay sands D1, D2 at depth of 7800 – 78100ft in the field.  

scholarly journals GEOPHYSICAL AND WELL CORELLATION ANALYSIS OF OGO FIELD: A CASE STUDY IN NIGER DELTA BASIN OF NIGERIA

2017 ◽  
Vol 36 (3) ◽  
pp. 729-733
Author(s):  
MO Ehigiator ◽  
NC Chigbata
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Average Porosity ◽  
Resistivity Logs ◽  
Hydrocarbon Formation ◽  
Formation Resistivity ◽  
Well Correlation ◽  
Niger Delta Basin ◽  
4D Seismic ◽  
Bottom To Top

A suite of geophysical wire line logs were run in hole. The wells data were acquired from bottom to top and not top to bottom. Basically, we have the qualitative and the quantitative evaluation techniques.Qualitative means is usually used for identification of the type of lithology and also for the component of the formation. Quantitative is used to estimate numerically, the value of what is in the formation. The logs used for evaluation were: Spontaneous potential logs and the Gamma ray logs. These were used to determine the lithology of the formation. Resistivity logs were run in hole to also determine the water saturation in the formation. The Formation Density and the compensated Neutron logs were run in hole to differentiate the gaseous zone from the oil zone in the Hydrocarbon Formation Ogo1, Ogo2 and Ogo3 from well correlation depicts that the subsurface stratigraphy is that of sand – shale intercalations.  Two prominent hydrocarbon bearing reservoirs (R1and R2), at Depth 1563m and 1642mm respectively were identified. The reservoirs were found to have average porosity of 0.22, water saturation 0.43 and Hydrocarbon saturation of 0.57. The reservoirs have permeability of 1376m, volume of oil in place for reservoir 1 and 2 is 39900m3  and 9647 m3   respectively. More. Well correlations are recommended for proper drilling and well completions. 4D seismic acquisitions should be encouraged for proper view of the formation. http://dx.doi.org/10.4314/njt.v36i3.10

scholarly journals 3-D Seismic Structural Interpretation of High Field Offshore Western Niger Delta

2021 ◽  
Vol 25 (8) ◽  
pp. 1361-1369
Author(s):  
S.S. Adebayo ◽  
E.O. Agbalagba ◽  
A.I. Korode ◽  
T.S. Fagbemigun ◽  
O.E. Oyanameh ◽  
...  
Keyword(s):  
Niger Delta ◽  
High Field ◽  
Gamma Ray ◽  
Tectonic Setting ◽  
Source Rocks ◽  
Structural Interpretation ◽  
Resistivity Logs ◽  
Seismic Sections ◽  
Niger Delta Basin ◽  
Structural Closure

Seismic Structural interpretation of subsurface system is a vital tool in mapping source rocks and good trapping system which enhances good understanding of the subsurface system for productive drilling operation. This study is geared towards mapping the structural traps available within the hydrocarbon bearing zones of the “High field” with the use of well log and 3D seismic data. Seven horizons (H1, H2, H3, H4, H5, H6 and H7) were identified on well logs using gamma ray log and resistivity logs. Nine (9) faults were mapped on seismic sections across the field, two (2) of which are major growth faults (F1 and F2), two (2) synthetic faults (F3 and F7) and five (5) antithetic faults (F4, F5, F6, F8 and F9). Rollover anticlines which are structural closure and displayed on the depth structural maps suggest probable hydrocarbon accumulation at the down throw side of the fault F1. Structural interpretation of high field has revealed a highly fault assisted reservoir which depicts the tectonic setting of Niger Delta basin.

scholarly journals Neural Network Prediction of P-wave Log for Reservoir Characterization in the Niger Delta Basin

2020 ◽  
Vol 17 (1) ◽  
pp. 28-32
Author(s):  
A. Ogbamikhumi ◽  
S.A. Salami ◽  
W.N. Uwadiae
Keyword(s):  
Neural Network ◽  
Correlation Coefficient ◽  
Reservoir Characterization ◽  
Gamma Ray ◽  
P Wave ◽  
Wave Parameter ◽  
Estimation Methods ◽  
Sonic Log ◽  
Neural Network Prediction ◽  
Niger Delta Basin

This study present a new technique that integrates several logs for P-wave prediction to minimize some errors and uncertainties associated with most estimation methods. The adopted method involves application of an artificial neural network technique that integrates density, resistivity and gamma ray logs for data training and the prediction of P-wave log. The results obtained gave correlation coefficient of 0.77, 0.24 and 0.42 between the acquired P-wave log and the acquired density, resistivity and gamma ray logs respectively, to demonstrate the relationship between P-wave log and the selected logs for the prediction process. The correlation coefficient of the estimated P-wave from Gardner and Faust methods with the acquired P-wave log are 0.64 and 0.59 respectively, while that of the neural network derived P-wave gave a better correlation coefficient of 0.81. Cross plot validation of P-wave derive Acoustic Impedance against density for both lithology and fluid discrimination revealed clusters for neural network derived P-wave parameter similar to the acquired P-wave derived parameters. Results of the presented neural network technique have been demonstrated to be more effective than results of the two conventional techniques. Keywords: Sonic log, Gardner’s method, Faust method, Neural network, Cross plot.

scholarly journals Evaluation of Petrophysical Parameters of Reservoir Sand Wells in Uzot-Field, Onshore Niger Delta Basin, Nigeria

2021 ◽  
Vol 25 (2) ◽  
pp. 157-171
Author(s):  
UC Omoja ◽  
T.N. Obiekezie
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Depth Range ◽  
High Hydrocarbon ◽  
Hydrocarbon Production ◽  
Petrophysical Parameters ◽  
Resistivity Logs ◽  
Hydrocarbon Saturation ◽  
Niger Delta Basin ◽  
Sand Bodies

Evaluation of the petrophysical parameters in Uzot-field was carried out using Well log data. The target for this study was the D3100 reservoir sand of wells Uz 004, Uz 005, U008 and Uz 011 with depth range of 5540ft to 5800ft across the four wells. Resistivity logs were used to identify hydrocarbon or water-bearing zones and hence indicate permeable zones while the various sand bodies were then identified using the gamma ray logs. The results showed the delineated reservoir units having porosity ranging from 21.40% to 33.80% indicating a suitable reservoir quality; permeability values from 1314md to 18089md attributed to the well sorted nature of the sands and hydrocarbon saturation range from 12.00% to 85.79% implying high hydrocarbon production. These results suggest a reservoir system whose performance is considered satisfactory for hydrocarbon production. Keywords: Petrophysical parameters, porosity, permeability, hydrocarbon saturation, Niger Delta Basin

scholarly journals Petrophysical Properties of the Upper Qamchuqa Carbonate Reservoir through Well Log Evaluation in the Khabbaz Oilfield

2017 ◽  
Vol 1 (1) ◽  
pp. 72-88 ◽  
Author(s):  
Ala A. Ghafur ◽  
Dana A. Hasan
Keyword(s):  
Gamma Ray ◽  
Size Structure ◽  
Water Saturation ◽  
Carbonate Reservoir ◽  
High Porosity ◽  
Petrophysical Properties ◽  
Log Data ◽  
Reservoir Characteristics ◽  
Sonic Log ◽  
Resistivity Logs

Khabbaz oilfield has a symmetrical subsurface anticline with a length of 20 km and a width of 4 km. Despite the fact that Khabbaz oilfield has a small size structure, it is known as one of the massive Oilfields in Iraq. The reservoirs of Khabbaz oilfield are produced by both Cretaceous and Tertiary rocks. The Upper Qamchuqa reservoir is the most productive reservoir of the Khabbaz oilfield with thickness ranges between 138 to 170 m. This formation is subdivided into two units, from the top is Unit A with a thickness of 67 m and from the bottom is Unit B with a thickness of 84.5 m. From a full set of log data of three wells (Kz-1, Kz-13 and Kz-14), the petrophysical properties of Khabbaz oilfield has been evaluated. The wireline log data includes gamma-ray log, sonic log, neutron log, density log and resistivity logs, both Rxo and Rt logs. This study revealed that Unit A represents the best reservoir characteristics where Unit A is subdivided into six reservoir subunits named (1-A, 2-A, 3-A, 4-A, 5-A and 6-A). They are separated by five non-reservoir subunits named 1-N, 2-N, 3-N, 4-N and 5-N. In addition to a less porous reservoir unit that is called Unit B, which has been divided into four reservoir subunits named 1-B, 2-B, 3-B and 4-B. These are separated by five non-reservoir units named 1-N, 2-N, 3-N, 4-N and 5-N. It has been recognized that both reservoir units A and B are clean formations and have minimum shale volume with high porosity in limestone and dolomite to dolomitic limestone lithology with high oil saturation and low water saturation. Based on the above reservoir characteristics it can be concluded that the reservoir units of the Khabbaz oilfield contain a massive commercial hydrocarbon accumulation.

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