scholarly journals Development of an Appropriate Model for predicting Pore Pressure in Niger delta, Nigeria using Offset Well Data

2019 ◽  
Vol 3 (1) ◽  
pp. 274-279
Author(s):  
Abubakar Tanko ◽  
Kelani Bello ◽  
Idris Tanko
Keyword(s):  
Pore Pressure ◽  
Niger Delta ◽  
Well Data

scholarly journals Investigation of Pore Pressure on Seismic Amplitude Response: A Well-Based Modeling Case Study of Sojuko Field, Niger Delta

2019 ◽  
Vol 11 (3) ◽  
pp. 36
Author(s):  
Difference O. Ogagarue
Keyword(s):  
Pore Pressure ◽  
Niger Delta ◽  
Oil Sands ◽  
Hydrocarbon Exploration ◽  
Pressure Effects ◽  
Reflection Coefficients ◽  
Angle Of Incidence ◽  
Offshore Area ◽  
Seismic Amplitude ◽  
Well Data

The Sojuko field was discovered in 2001 in the eastern shallow offshore area of the Niger Delta, Nigeria. Three (3) exploration wells have so far been drilled in the field, two (2) of which are reasonably vertical and the third highly deviated. Three (3) key reservoirs which are laterally continuous across the wells have been identified with proven oil and gas reserves. Pore pressure data from repeat formation test (RFT) measurements acquired in the deviated well show that the wells are entirely hydrostatic to true depth (TD). This research focuses on investigating how seismic amplitudes change with offset/angle of incidence in relation to varying pore pressure regimes at the shale-hydrocarbon sand and shale-brine sand interfaces using well data. The aim is to aid quantitative interpretation in an on-going field-wide exploration drive to de-risk hydrocarbon exploration in the deeper plays in the area which are below TD, and are expected to be overpressured. The study is hinged on end-member shale elastic parameter substitution in which the shales are subjected to varying overpressure regimes while keeping the reservoirs (sands) at in situ (hydrostatic) condition. The end-member shale property substitution simulated shale compaction dis-equilibrium as the main overpressure generation mechanism in this study. The results show that top gas sands, top oil sands and top brine sands would be visible on seismic in the deeper plays where pore pressures are expected to be very high, but with distinctive seismic amplitude with offset/angle behavior. The top gas sands are visible as blue loop with small positive reflection coefficients at the near offsets/angles, but with polarity reversal to red loop with negative reflection coefficients which become more and more negative at the far angles at hard overpressure regimes. Top oil sands are recognized as blue loop with large positive reflection coefficients at the near angles; the coefficients becoming less and less positive at the far angles/offsets. The top oil sands may not be detected on seismic at the far angles/offsets unless at very hard overpressures. Brine sands have similar seismic response as oil sands at hard overpressures, but can be distinguished from oil sands based on their much higher amplitudes over the entire offset/angle range. The study is also aimed at removing uncertainty in seismic-based pore pressure quantification at the deeper targets where there is absence of well data for calibrating pore pressure effects at varying conditions.

Application of Machine Learniing For Reservoir Facies Classification in Port Field, Offshore Niger Delta

2021 ◽  
Author(s):  
Jerome Asedegbega ◽  
Oladayo Ayinde ◽  
Alexander Nwakanma
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Niger Delta ◽  
Nearest Neighbor ◽  
Support Vector ◽  
Data Preparation ◽  
K Nearest Neighbor ◽  
Blind Test ◽  
Facies Classification ◽  
Well Data

Abstract Several computer-aided techniques have been developed in recent past to improve interpretational accuracy of subsurface geology. This paradigm shift has provided tremendous success in variety of Machine Learning Application domains and help for better feasibility study in reservoir evaluation using multiple classification techniques. Facies classification is an essential subsurface exploration task as sedimentary facies reflect associated physical, chemical, and biological conditions that formation unit experienced during sedimentation activity. This study however, employed formation samples for facies classification using Machine Learning (ML) techniques and classified different facies from well logs in seven (7) wells of the PORT Field, Offshore Niger Delta. Six wells were concatenated during data preparation and trained using supervised ML algorithms before validating the models by blind testing on one well log to predict discrete facies groups. The analysis started with data preparation and examination where various features of the available well data were conditioned. For the model building and performance, support vector machine, random forest, decision tree, extra tree, neural network (multilayer preceptor), k-nearest neighbor and logistic regression model were built after dividing the data sets into training, test, and blind test well data. Results of metric score for the blind test well estimated for the various models using Jaccard index and F1-score indicated 0.73 and 0.82 for support vector machine, 0.38 and 0.54 for random forest, 0.78 and 0.83 for extra tree, 0.91 and 0.95 for k-nearest neighbor, 0.41 and 0.56 for decision tree, 0.63 and 0.74 for logistic regression, 0.55 and 0.68 for neural network, respectively. The efficiency of ML techniques for enhancing the prediction accuracy and decreasing the procedure time and their approach toward the data, makes it importantly desirable to recommend them in subsurface facies classification analysis.

scholarly journals Drilling Optimization of Tight Sands and Shale Gas Reservoir in Jambi Sub-Basin Based on Pore Pressure Estimation Using Drilling Efficiency Mechanical Specific Energy (DEMSE) and Bowers Methods

2019 ◽  
Vol 125 ◽  
pp. 15001
Author(s):  
Benny Abraham Bungasalu ◽  
M. Syamsu Rosid ◽  
Don S. Basuki
Keyword(s):  
Pore Pressure ◽  
Specific Energy ◽  
Shale Gas ◽  
Seismic Inversion ◽  
Mechanical Specific Energy ◽  
Drilling Operations ◽  
Well Data ◽  
Tight Sand Gas ◽  
Productive Time ◽  
Pressure Analysis

The subsurface pressure analysis is used to detect the overpressure and problems in the well that will be drilled based on exploration well data. Various problems were found while drilling operations carried out on A and B wells, namely, Kick and Pipe sticking which cause a high Non-Productive Time (NPT). This research is conducted to identify the mechanism of overpressure formation in Tight Sand Gas and Shale Gas in the Jambi Sub-Basin. Furthermore, to predict pore pressure using the Drilling Efficiency and Mechanical Specific Energy (DEMSE) and Bowers method. The final result will be a 3D pore pressure cube in the area based on quantitative analysis of post-stack seismic inversion. The results of the pore pressure analysis from the wells and the 3D pore pressure model indicate that top of overpressure occurs in the Gumai Formation, then it is decreasing gradually approaching the hydrostatic pressure on the Basement. The mechanisms of overpressure are caused by under compaction, fluid expansion (kerogen maturation). The Gumai Formation and Talang Akar Formation are shale rocks so the type of mud weight that is well used is oil based mud (OBM).

Seismic pore pressure prediction without well data and poorly defined normal compaction trend lines: a case study from the Río Bravo Delta, Northern Mexico

2005 ◽  
Author(s):  
Juan C. Clarembaux ◽  
Marcelo Giusso ◽  
Roberto Gullco ◽  
Daniel Mujica ◽  
Carlos Carabeo Miranda ◽  
...  
Keyword(s):  
Pore Pressure ◽  
Northern Mexico ◽  
Pore Pressure Prediction ◽  
Rio Bravo ◽  
Well Data

Bright spots, dim spots: Geologic controls of direct hydrocarbon indicator type, magnitude, and detectability, Niger Delta Basin

2016 ◽  
Vol 4 (3) ◽  
pp. SN45-SN69 ◽  
Author(s):  
Krzysztof M. Wojcik ◽  
Irene S. Espejo ◽  
Adebukonla M. Kalejaiye ◽  
Otuka K. Umahi
Keyword(s):  
Niger Delta ◽  
Soft Clay ◽  
Bright Spot ◽  
Systematic Analysis ◽  
Bright Spots ◽  
Key Factor ◽  
Well Data ◽  
Diagenetic Evolution ◽  
Niger Delta Basin ◽  
Fluid Signal

Bright-spot amplitude anomalies have been an attractive exploration target in the Niger Delta since the early 1970s, and the bright-spot play can now be considered mature. There is a need to extend the bright-spot exploration success to include other types of direct hydrocarbon indicators such as dim spots or polarity reversals. Several true dim spots have been identified in the basin, calibrated with well data and characterized in detail to enable a systematic analysis of the geologic factors that produce the dim-spot response. Dim spots in deeper stratigraphic intervals reflect a high degree of compaction and quartz cementation and are characterized by minimal fluid signal and commonly very low detectability. Robust and detectable dim spots have been identified in shallow marine/deltaic systems in the Niger Delta in shallower stratigraphic intervals with a relatively strong fluid signal. The key factor promoting a robust dim-spot response is the presence of acoustically soft, clay-rich shales as the bounding lithology. The variability of the bounding shales in the Niger Delta is stratigraphically constrained and, to some degree, predictable. The change from hard mudstones to soft claystones, which can be recognized in seismic data, may result in a transition from bright to dim spots, possibly taking place within the same stratigraphic interval and over short distances. Many clastic basins globally follow a similar stratigraphic and diagenetic evolution; thus, the Niger Delta example may be a good analog for dim-spot plays elsewhere.

scholarly journals Disequilibrium Compaction, Fluid expansion and unloading effects: Analysis from well log and its pore pressure implication in Jay Field, Niger Delta

2020 ◽  
pp. 389-400 ◽  
Author(s):  
Chukwuemeka Patrick Abbey ◽  
Meludu Chukwudi Osita ◽  
Oniku Adetola Sunday ◽  
Mamman Yusuf Dabari
Keyword(s):  
Acoustic Wave ◽  
Pore Pressure ◽  
Niger Delta ◽  
Sedimentary Basins ◽  
Burial Depth ◽  
Well Log ◽  
Major Mechanism ◽  
Porosity And Permeability ◽  
Well Log Analysis ◽  
Pressure Regime

     Disequilibrium compaction, sometimes referred to as under compaction, has been identified as a major mechanism of abnormal pore pressure buildup in sedimentary basins. This is attributed to the interplay between the rate at which sediments are deposited and the rate at which fluids associated with the sediments are expelled with respect to burial depth. The purpose of this research is to analyze the mechanisms associated with abnormal pore pressure regime in the sedimentary formation. The study area “Jay field” is an offshore Niger Delta susceptible to abnormal pore pressure regime in the Agbada –Akata formations of the basin. Well log analysis and cross plots were applied to determine the under compacted zone in the formation since compaction increases with burial depth. It was observed that porosity and permeability of the deeper depth (3700 m to end of Well) are higher than those of the shallow part (3000 – 3700 m). This is against what is expected from normal compacted sediment, demonstrating disequilibrium compaction in deposition. Furthermore, it reveals that sedimentation rate was high, making it unable for the sediments to expunge its fluid as expected. Density and acoustic wave increase with depth in normal compaction trend. However, the reverse that was identified in the mapped interval is attributed to disequilibrium compaction, unloading, clay diagenesis, and fluid expansion. The cross plot divulges sediments at the deeper depth had lower density and acoustic wave value with increased porosity when compared to those at shallow depth. This forms the basis that the sediments from this mapped interval experienced disequilibrium and unloading traceable to clay diagenesis during and after deposition, respectively.

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