Coblending of seismic attributes for interpretation of channel geometries in Rence Field of Niger Delta, Nigeria

2015 ◽  
Vol 3 (4) ◽  
pp. T183-T195 ◽  
Author(s):  
Augustine Ifeanyi Chinwuko ◽  
Ajana Godwin Onwuemesi ◽  
Emmanuel Kenechukwu Anakwuba ◽  
Clement Udenna Onyekwelu ◽  
Harold Chinedu Okeke ◽  
...  
Keyword(s):  
Niger Delta ◽  
Water Saturation ◽  
Seismic Attributes ◽  
Hydrocarbon Exploration ◽  
Seismic Facies ◽  
Petrophysical Analysis ◽  
Net To Gross ◽  
Seismic Facies Analysis ◽  
Well Data ◽  
Channel Deposits

Coblending of seismic attributes is used in the interpretation of channel geometries in the Rence Field of Niger Delta, Nigeria. We aimed at seismically defining the geometries of hydrocarbon reservoirs with particular emphasis on channels in the shallow marine (offshore) Niger Delta. The coblending application enhanced the ease of detection and the continuity of the channels, leaving the channel environs unchanged. The result of the seismic facies analysis revealed that the Rence Field can be distinguished into two seismic facies, namely, layered complexes and chaotic complexes. The result of well to seismic ties revealed high- and low-amplitude reflection events for sand and shale units, respectively. Seismic structural interpretation of the Rence Field revealed 4 major regional faults and 12 minor faults. Seven of the faults were antithetic, and the rest were synthetic faults. One mega-channel feature that trends east–west was identified in the attribute maps generated. It was characterized by sinuosity of 1.3, with a length of 22,500 m, and a distance of 17,500 m. The average depth of the channel was approximately 170 m with amplitude of 1670 m and the wavelength as high as 7640 m. A depositional model generated from the attribute maps indicated a prograding fluvial environment of deposition. The attribute map also determined that there was shifting in the location of barrier bars within the area. This shifting could be attributed to the growth fault mechanism. At the stoss side of the sinusoidal channel, there were prominent sand point bar sequences. The petrophysical analysis of the well data revealed 90% net-to-gross, 28% porosity, 27% volume of shale, and 24% water saturation indicating that the reservoir was of pay quality. Based on the petrophysical analysis, results, and identification of channel deposits, the study area proved highly promising for hydrocarbon exploration.

scholarly journals Hydrocarbon Reservoir Evaluation: a case study of Tymot field at southwestern offshore Niger Delta Oil Province, Nigeria

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Victor Cypren Nwaezeapu ◽  
Izediunor U. Tom ◽  
Ede T. A. David ◽  
Oguadinma O. Vivian
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Water Saturation ◽  
Reservoir Evaluation ◽  
Hydrocarbon Reservoir ◽  
Structural Style ◽  
Average Porosity ◽  
Net To Gross ◽  
Well Data

Abstract: Aim: This study presents the log analysis results of a log suite comprising gamma ray (GR), resistivity (LLD), neutron (PHIN), density (RHOB) logs and a 3D seismic interpretation of Tymot field located in the southwestern offshore of Niger delta. This study focuses essentially on reserves estimation of hydrocarbon bearing sands. Well data were used in the identification of reservoirs and determination of petrophysical parameters and hydrocarbon presence. Three horizons that corresponded to selected well tops were mapped after well-to-seismic tie. Structural depth maps were created from the mapped horizons. The structural style is dominated by widely spaced simple rollover anticline bounded by growth faults, and this includes down-to-basin faults, antithetic faults and synthetic faults. The petrophysical values – the porosity, net-to-gross, water saturation, hydrocarbon saturation that were calculated yielding  an average porosity value  of 0.23, water saturation of 0.32 and an average net-to-gross value of 0.62. Three horizons H1, H2 and H3 were mapped. The three horizons marked the tops of reservoir sands and provide the structures for hydrocarbon accumulation. Hydrocarbon in-place was estimated. The total hydrocarbon proven reserves for the mapped horizons H1, H2, and H3 were estimated to be 39.04MMBO of oil and 166.13BCF for sand E. 

3-D Seismic Interpretation and Volumetric Estimation of “Osaja Field” Niger Delta, Nigeria

2016 ◽  
Vol 59 ◽  
pp. 14-28
Author(s):  
Lawson Jack Osaki ◽  
Alexander Iheanyichukwu Opara ◽  
Chikwendu Njoku Okereke ◽  
Uche Petters Adiela ◽  
Ikechukwu Onyema Njoku ◽  
...  
Keyword(s):  
Niger Delta ◽  
Reservoir Characterization ◽  
Water Saturation ◽  
Seismic Interpretation ◽  
Structural Interpretation ◽  
Petrophysical Analysis ◽  
Volumetric Estimation ◽  
Net To Gross ◽  
Original Oil In Place ◽  
Structural Architecture

3-D seismic interpretation and petrophysical analysis of the Osaja Field, Niger Delta, was carried out with aim of carrying out a detailed structural interpretation, reservoir characterization and volumetric estimation of the field. Four wells were correlated across the field to delineate the lithology and establish the continuity of reservoir sand as well as the general stratigraphy of the area. The petrophysical analysis carried out, revealed two sand units that are hydrocarbon bearing reservoirs (Sand_A and Sand_B).The spatial variation of the reservoirs were studied on a field wide scale using seismic interpretation. Time and depth structural maps generated were used to establish the structural architecture/geometry of the prospect area of the field. The depth structure map revealed NE-SW trending anticlinal structures with F5and F6as faults assisted closures to the reservoir. Furthermore, reservoir parameters such as net pay, water saturation porosity, net-to-gross etc, were derived from the integration of seismic and well log data. The structural interpretation on the 3-D seismic data of the study area revealed a total of seven faults ranging from synthetic to antithetic faults. The petrophysical analysis gave the porosity values of the reservoir Sand_A ranging from 18.1 - 20.3% and reservoir Sand_B ranging from 13.1-14.9% across the reservoir. The permeability values of reservoir Sand_A ranging from 63-540md and reservoir Sand_B ranging from 18-80md hence there is decrease in porosity and permeability of the field with depth.The net-to-gross varies from 22.1% to 22.4% in Rerservoir Sand A to between 5.34- 12% for Rerservoir Sand _A while Sw values for the reservoirs ranges from 38-42% in well 2 to about 68.79-96.06% in well 11. The result of original oil in place for all the wells calculated revealed that well 2 has the highest value with 9.3mmbls. These results indicate that the reservoirs under consideration have a poor to fair hydrocarbon (oil) prospect.

scholarly journals Characterization and geostatistical modeling of reservoirs in ‘Falad’ field, Niger Delta, Nigeria

2021 ◽  
Author(s):  
Ayodele O. Falade ◽  
John O. Amigun ◽  
Yousif M. Makeen ◽  
Olatunbosun O. Kafisanwo
Keyword(s):  
Niger Delta ◽  
Structural Model ◽  
Water Saturation ◽  
Sequential Gaussian Simulation ◽  
Surface Generation ◽  
Geostatistical Modeling ◽  
Reservoir Properties ◽  
Field Development ◽  
Net To Gross ◽  
Well Data

AbstractThis research aims at characterizing and modeling delineated reservoirs in ‘Falad’ Field, Niger Delta, Nigeria, to mitigate the challenge caused by the heterogeneous nature of the reservoirs. Seismic and well log data were integrated, and geostatistics was applied to describe the reservoir properties of the interwell spaces within the study area. Four reservoirs, namely RES 1, RES 2, RES 3 and RES 4, were delineated and correlated across four wells. The reservoir properties {lithology, net to gross, porosity, permeability, water saturation} of all the delineated reservoirs mapped were determined, and two reservoirs with the best quality were picked for further analysis (surface generation and modeling) after ranking the reservoirs based on their quality. Structural interpretation of the field was carried, nine faults were mapped (F1—F9), and the fault polygon was generated. The structural model showed the area is structurally controlled with two of the major faults mapped (F1 and F3) oriented in the SW–NE direction while the other one (F4) is oriented in the NW–SE direction. A 3D grid was constructed using the surfaces of the delineated reservoirs and the reservoir properties were distributed stochastically using simple krigging method with sequential Gaussian simulation, sequential indicator simulation and Gaussian random function simulation algorithms. Geostatistical modeling used in this study has been able to give subsurface information in the areas deficient of well data as the estimated reservoir properties gotten from existing wells have been spatially distributed in the study area and will thus aid future field development while also they are used in identifying new prospect by combining property models with structural maps of the area.

SEISMIC FACIES ANALYSIS AND STRUCTURAL INTERPRETATION OF DEEPWATER NW SABAH

2015 ◽  
Vol 75 (1) ◽  
Author(s):  
Mohd Akhmal Muhamad Sidek ◽  
Umar Hamzah ◽  
Radzuan Junin
Keyword(s):  
Gamma Ray ◽  
Hydrocarbon Exploration ◽  
Seismic Facies ◽  
Tectonic Event ◽  
Structural Interpretation ◽  
Tectonic Events ◽  
Regional Tectonic ◽  
Seismic Facies Analysis ◽  
Sequence Boundaries ◽  
Seismic Lines

The deepwaters of NW Sabah has been an interesting site for deepwater hydrocarbon exploration in Malaysia. Up to now, the exploration in this is mainly focused to the Late Miocene until the Pliocene siliciclastic sediment reservoirs distribution at the shelf edge. This paper shows a gross seismic facies mapping analysis and structural interpretation of regional deepwater NW Sabah especially at Sabah Trough. To convert depth, all seismic lines were picked and tied with selected wells. The results of the interpretation were then summarized and presented with relation to regional tectonic events. Eight seismic stratigraphic units, six seismic facies together with five sequence boundaries were recognized. Multichannel reflection 2D seismic data, gamma ray logs and biostratigraphy description from the three wells at deepwater fold-thrust belt and published tectono-stratigraphic scheme from Dangerous Grounds (Sabah Platform) in South China Sea were selected in this study. The propose of this study is to document the relevance of regional tectonic event between Dangerous Ground and Sabah Trough. 

A statistical methodology for deriving reservoir properties from seismic data

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1437-1450 ◽  
Author(s):  
Frédérique Fournier ◽  
Jean‐François Derain
Keyword(s):  
Seismic Data ◽  
Large Scale ◽  
Seismic Attributes ◽  
Seismic Facies ◽  
Reservoir Properties ◽  
Data Set ◽  
Analysis Technique ◽  
Seismic Facies Analysis ◽  
Statistical Relationships

The use of seismic data to better constrain the reservoir model between wells has become an important goal for seismic interpretation. We propose a methodology for deriving soft geologic information from seismic data and discuss its application through a case study in offshore Congo. The methodology combines seismic facies analysis and statistical calibration techniques applied to seismic attributes characterizing the traces at the reservoir level. We built statistical relationships between seismic attributes and reservoir properties from a calibration population consisting of wells and their adjacent traces. The correlation studies are based on the canonical correlation analysis technique, while the statistical model comes from a multivariate regression between the canonical seismic variables and the reservoir properties, whenever they are predictable. In the case study, we predicted estimates and associated uncertainties on the lithofacies thicknesses cumulated over the reservoir interval from the seismic information. We carried out a seismic facies identification and compared the geological prediction results in the cases of a calibration on the whole data set and a calibration done independently on the traces (and wells) related to each seismic facies. The later approach produces a significant improvement in the geological estimation from the seismic information, mainly because the large scale geological variations (and associated seismic ones) over the field can be accounted for.

scholarly journals A New Method To Estimate Resistivity Distribution Of Shaly Sand Reservoirs Using New Seismic Attributes

2021 ◽  
Vol 71 ◽  
pp. 149-157
Author(s):  
Nur Farhana Salleh ◽  
◽  
Maman Hermana ◽  
Deva Prasad Ghosh
Keyword(s):  
Water Saturation ◽  
Seismic Attributes ◽  
Effective Porosity ◽  
Seismic Attenuation ◽  
Hydrocarbon Exploration ◽  
Fluid Distribution ◽  
Similar Response ◽  
Petrophysical Properties ◽  
Resistivity Model ◽  
Shaly Sand

A subsurface resistivity model is important in hydrocarbon exploration primarily in the controlled-source electromagnetic (CSEM) method. CSEM forward modelling workflow uses resistivity model as the main input in feasibility studies and inversion process. The task of building a shaly sand resistivity model becomes more complex than clean sand due to the presence of a shale matrix. In this paper, a new approach is introduced to model a robust resistivity property of shaly sand reservoirs. A volume of seismic data and three wells located in the K-field of offshore Sarawak is provided for this study. Two new seismic attributes derived from seismic attenuation property called SQp and SQs are used as main inputs to predict the volume of shale, effective porosity, and water saturation before resistivity estimation. SQp attribute has a similar response to gamma-ray indicating the lithological variation and SQs attribute is identical to resistivity as an indicator to reservoir fluids. The petrophysical predictions are performed by solving the mathematical step-wise regression between the seismic multi-attributes and predicted petrophysical properties at the well locations. Subsequently, resistivity values are estimated using the Poupon-Leveaux (Indonesia) equation, an improvised model from Archie’s to derive the mathematical relationship of shaly sand’s resistivity to the volume and resistivity of clay matrix in shaly sand reservoirs. The resistivity modeled from the predicted petrophysical properties distributed consistently with sand distribution delineated from SQp attribute mainly in southeast, northeast, and west regions. The gas distribution of the net sand modeled by 5% and 90% of gas saturation scenarios also changed correspondingly to SQs attribute anomaly indicating the consistent fluid distribution between the modeled resistivity and SQs attribute.

scholarly journals Petrophysical Analysis of ‘Bright’ Field, Onshore Niger Delta

2021 ◽  
Keyword(s):  
Niger Delta ◽  
Gamma Ray ◽  
Water Saturation ◽  
Research Work ◽  
Accurate Estimation ◽  
Bright Field ◽  
Petrophysical Analysis ◽  
Lithology Identification ◽  
Resistivity Logs ◽  
Sand Bodies

Petrophysical analysis is key to the success of any oil exploration and exploitation work and this task requires evaluation of the reservoir parameters in order to enhance accurate estimation of the volume of oil in place. This research work involves the use of suite of well logs from 4-wells to carry out the petrophysical analysis of ‘Bright’ Field Niger Delta. The approach used includes lithology identification, reservoir delineation and estimation of reservoir parameters. Two sand bodies were mapped across the entire field showing their geometry and lateral continuity, gamma ray and resistivity logs were used to delineate the reservoirs prior to correlation and relevant equations were used to estimate the reservoir parameters. The result of the petrophysical analysis showed variations in the reservoir parameters within the two correlated sand bodies with high hydrocabon saturation in sand 1 well 1 while the remaining wells within the correlated wells are water bearing. The porosity values range from 0.19 to 0.32, volume of shale from 0.15 to 0.40, water saturation from 0.20 to 0.92 for the sand bodies.

Seismic facies classification using supervised convolutional neural networks and semisupervised generative adversarial networks

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. O47-O58 ◽  
Author(s):  
Mingliang Liu ◽  
Michael Jervis ◽  
Weichang Li ◽  
Philippe Nivlet
Keyword(s):  
Neural Networks ◽  
Seismic Data ◽  
Hydrocarbon Exploration ◽  
Training Data ◽  
Seismic Facies ◽  
Generative Adversarial Networks ◽  
Complex Data ◽  
Facies Classification ◽  
Good Ability ◽  
Well Data

Mapping of seismic and lithologic facies from 3D reflection seismic data plays a key role in depositional environment analysis and reservoir characterization during hydrocarbon exploration and development. Although a variety of machine-learning methods have been developed to speed up interpretation and improve prediction accuracy, there still exist significant challenges in 3D multiclass seismic facies classification in practice. Some of these limitations include complex data representation, limited training data with labels, imbalanced facies class distribution, and lack of rigorous performance evaluation metrics. To overcome these challenges, we have developed a supervised convolutional neural network (CNN) and a semisupervised generative adversarial network (GAN) for 3D seismic facies classification in situations with sufficient and limited well data, respectively. The proposed models can predict 3D facies distribution based on actual well log data and core analysis, or other prior geologic knowledge. Therefore, they provide a more consistent and meaningful implication to seismic interpretation than commonly used unsupervised approaches. The two deep neural networks have been tested successfully on a realistic synthetic case based on an existing reservoir and a real case study of the F3 seismic data from the Dutch sector of the North Sea. The prediction results show that, with relatively abundant well data, the supervised CNN-based learning method has a good ability in feature learning from seismic data and accurately recovering the 3D facies model, whereas the semisupervised GAN is effective in avoiding overfitting in the case of extremely limited well data. The latter seems, therefore, particularly adapted to exploration or early field development stages in which labeled data from wells are still very scarce.

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