scholarly journals Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

2021 ◽  
pp. 1943-1955
Author(s):  
Ahmed Muslim Khawaja ◽  
Jassim Muhammad Thabit
Keyword(s):  
Low Frequency ◽  
Depositional Environments ◽  
Oil Field ◽  
Frequency Model ◽  
Environment Model ◽  
Carbonate Formation ◽  
Porous Reservoir ◽  
Well Data ◽  
Isopach Map ◽  
Marine Basin

In this paper, we attempt to predict the depositional environments with associated lithofacies of the main reservoir of the late Cretaceous Mishrif carbonate Formation, depending on the analysis of the created seismic isopach map by integrating seismic and well data. The isopach map was created from a 3D-seismic reflection survey carried out at the Dujaila oil field in southeastern Iraq, which is of an area of 602.26 Km2, and integrated with the data of the two explored wells. Based on the interpretation of the seismic isopach map, the diagram of the 3D-depositional environment model of Mishrif Formation was constructed. It showed three distinguished depositional environments, which were graduated from a back reef lithofacies of a shallow open marine (shelf) environment in the west and NW, to a shoal environment of isolated Rudist reefal buildup in the middle, and a fore reef lithofacies of the deep open marine basin environment in the SE of the field. A 3D-instantaneous frequency model was generated to verify the capability of the seismic isopach map of predicting the depositional environments, which in turn showed that the low frequency was restricted in the region of the high thickness of Rudist reefal buildups (porous reservoir facies) in the vicinity of the productive well Dujaila-1.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

Improved seismic inversion and reservoir description of the Ichthys gas-condensate field, Browse Basin, Western Australia

2010 ◽  
Vol 50 (2) ◽  
pp. 716
Author(s):  
Masamichi Fujimoto ◽  
Takeshi Yoshida ◽  
Andrew Long
Keyword(s):  
Low Frequency ◽  
Seismic Inversion ◽  
Gas Condensate ◽  
Sensor Technology ◽  
Frequency Model ◽  
Porosity Distribution ◽  
Low Frequencies ◽  
Simultaneous Inversion ◽  
Dual Sensor ◽  
Well Data

Seismic inversion has become a standard geophysical tool to enhance seismic resolution, predict the reservoir porosity distribution, and to discriminate between reservoir and non-reservoir pay zones. Conventional seismic data does not record the low frequencies necessary for inversion. To enable a complete bandwidth, low frequencies are modelled from well data and are typically interpolated throughout the volume using seismic velocities. This often causes the resultant porosity distribution calculated from the inverted P-impedance to be biased by the well data and the geometry of well locations. Dual-sensor GeoStreamer technology was used to acquire a regional multi-client 2D survey by PGS in 2008, including some lines over the Ichthys gas-condensate field in the Browse Basin. Dual-sensor streamer processing recovers a wider frequency bandwidth than conventional seismic. Receiver ghost removal combined with deep streamer towing simultaneously boosts both the low and high frequencies. The improved bandwidth enables a higher quality of velocity analysis, which further improves resolution throughout the section. Simultaneous inversion of the data validated the uplift of the low frequency data, and significantly reduced the bias towards well data for the low frequency model. The resultant P-impedance data demonstrated an excellent tie to well data. The dual-sensor technology promises to improve the description of the porosity distribution within our reservoir model.

scholarly journals The Use of Gamma Ray Log Data to Compute and Study the Deposition of Shale Volume of Mishrif Formation in Middle and Southern Parts of Iraq

2021 ◽  
pp. 3932-3941
Author(s):  
Hiba Tarq Jaleel ◽  
Ahmed S. Al-Banna ◽  
Ghazi H. Al-Sharaa
Keyword(s):  
Gamma Ray ◽  
Oil Field ◽  
Log Data ◽  
Shale Volume ◽  
Carbonate Formation ◽  
Regional Area ◽  
Isopach Map ◽  
Gamma Ray Log ◽  
Surfer Software

The shale volume is one of the most important properties that can be computed depending on gamma ray log. The shale volume of Mishrif Formation (carbonate formation from middle Cenomanian- early Turonian) was studied for the regional area of the middle and southern parts of Iraq. The gamma ray log data from seventeen  wells ( Kf-3,Kf-4, Ad-1,Ad -2,Dh-1, Bu-47, Ns-2, Ns-4, Am-1,Am-2,Hf-2,Hf-115,Mj-3,Mj-15, Su-7,Wq-15 and  Lu-7) distributed in the study area were used to compute the shale volume of Mishrif Formation. From the available data of the considered wells, a regional isopach map of Mishrif Formation was obtained. The isopach map indicates that the maximum thickness of Mishrif Formation is located at the eastern part of the study area. The results of the CPI and the shale volume map, which were computed using the Techlog and surfer software,  show that the maximum value of shale volume is located at the southern part of the study area (Su-7  well), while the minimum value is at the eastern  part (Hf-2well). According to the classification of Kamel and Mabrouk (2003), Mishrif Formation seems to be a Shaly Formation in the study area, except Halfaya oil field at the eastern part of the study area, which seems as a Clear Formation. The top map of the shale marker bed, which appears in most studied wells, shows a regional trend of the formation toward the northeast. According to the variation of the thickness of the shale marker bed, the study area is divided into four zones.

Modeling processed seismic data to improve seismic facies prediction

2015 ◽  
Vol 3 (4) ◽  
pp. SAC91-SAC98 ◽  
Author(s):  
Adrian Pelham
Keyword(s):  
Seismic Data ◽  
Confusion Matrix ◽  
Low Frequency ◽  
Rock Physics ◽  
Seismic Facies ◽  
Reservoir Modeling ◽  
Elastic Parameters ◽  
Frequency Model ◽  
Lithology Prediction ◽  
Well Data

Interpreters need to screen and select the most geologically robust inversion products from increasingly larger data volumes, particularly in the absence of significant well control. Seismic processing and inversion routines are devised to provide reliable elastic parameters ([Formula: see text] and [Formula: see text]) from which the interpreter can predict the fluid and lithology properties. Seismic data modeling, for example, the Shuey approximations and the convolution inversion models, greatly assist in the parameterization of the processing flows within acceptable uncertainty limits and in establishing a measure of the reliability of the processing. Joint impedance facies inversion (Ji-Fi®) is a new inversion methodology that jointly inverts for acoustic impedance and seismic facies. Seismic facies are separately defined in elastic space ([Formula: see text] and [Formula: see text]), and a dedicated low-frequency model per facies is used. Because Ji-Fi does not need well data from within the area to define the facies or depth trends, wells from outside the area or theoretical constraints may be used. More accurate analyses of the reliability of the inversion products are a key advance because the results of the Ji-Fi lithology prediction may then be quantitatively and independently assessed at well locations. We used a novel visual representation of a confusion matrix to quantitatively assess the sensitivity and uncertainty in the results when compared with facies predicted from the depth trends and well-elastic parameters and the well-log lithologies observed. Thus, using simple models and the Ji-Fi inversion technique, we had an improved, quantified understanding of our data, the processes that had been applied, the parameterization, and the inversion results. Rock physics could further transform the elastic properties to more reservoir-focused parameters: volume of shale and porosity, volumes of facies, reservoir property uncertainties — all information required for interpretation and reservoir modeling.

Prediction of Petrophysical Properties from Seismic Inversion and Neural Network: A case study

2021 ◽  
Author(s):  
Siddharth Garia ◽  
Arnab Kumar Pal ◽  
Karangat Ravi ◽  
Archana M Nair
Keyword(s):  
Neural Network ◽  
Bulk Density ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Well Log ◽  
Petrophysical Properties ◽  
Seismic Section ◽  
Frequency Model ◽  
Seismic Reflection Data ◽  
Reflection Data

<p>Seismic inversion method is widely used to characterize reservoirs and detect zones of interest, i.e., hydrocarbon-bearing zone in the subsurface by transforming seismic reflection data into quantitative subsurface rock properties. The primary aim of seismic inversion is to transform the 3D seismic section/cube into an acoustic impedance (AI) cube. The integration of this elastic attribute, i.e., AI cube with well log data, can thereafter help to establish correlations between AI and different petrophysical properties. The seismic inversion algorithm interpolates and spatially populates data/parameters of wells to the entire seismic section/cube based on the well log information. The case study presented here uses machine learning-neural network based algorithm to extract the different petrophysical properties such as porosity and bulk density from the seismic data of the Upper Assam basin, India. We analyzed three different stratigraphic  units that are established to be producing zones in this basin.</p><p> AI model is generated from the seismic reflection data with the help of colored inversion operator. Subsequently, low-frequency model is generated from the impedance data extracted from the well log information. To compensate for the band limited nature of the seismic data, this low-frequency model is added to the existing acoustic model. Thereafter, a feed-forward neural network (NN) is trained with AI as input and porosity/bulk density as target, validated with NN generated porosity/bulk density with actual porosity/bulk density from well log data. The trained network is thus tested over the entire region of interest to populate these petrophysical properties.</p><p>Three seismic zones were identified from the seismic section ranging from 681 to 1333 ms, 1528 to 1575 ms and 1771 to 1814 ms. The range of AI, porosity and bulk density were observed to be 1738 to 6000 (g/cc) * (m/s), 26 to 38% and 1.95 to 2.46 g/cc respectively. Studies conducted by researchers in the same basin yielded porosity results in the range of 10-36%. The changes in acoustic impedance, porosity and bulk density may be attributed to the changes in lithology. NN method was prioritized over other traditional statistical methods due to its ability to model any arbitrary dependency (non-linear relationships between input and target values) and also overfitting can be avoided. Hence, the workflow presented here provides an estimation of reservoir properties and is considered useful in predicting petrophysical properties for reservoir characterization, thus helping to estimate reservoir productivity.</p>

Poststack impedance inversion considering the diffractive component of the wavefield

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. R11-R28 ◽  
Author(s):  
Kun Xiang ◽  
Evgeny Landa
Keyword(s):  
Specular Reflection ◽  
Low Frequency ◽  
Velocity Model ◽  
Forward Modeling ◽  
Small Scale ◽  
Fracture Detection ◽  
Frequency Model ◽  
New Approach ◽  
Impedance Inversion ◽  
Diffraction Imaging

Seismic diffraction waveform energy contains important information about small-scale subsurface elements, and it is complementary to specular reflection information about subsurface properties. Diffraction imaging has been used for fault, pinchout, and fracture detection. Very little research, however, has been carried out taking diffraction into account in the impedance inversion. Usually, in the standard inversion scheme, the input is the migrated data and the assumption is taken that the diffraction energy is optimally focused. This assumption is true only for a perfectly known velocity model and accurate true amplitude migration algorithm, which are rare in practice. We have developed a new approach for impedance inversion, which takes into account diffractive components of the total wavefield and uses the unmigrated input data. Forward modeling, designed for impedance inversion, includes the classical specular reflection plus asymptotic diffraction modeling schemes. The output model is composed of impedance perturbation and the low-frequency model. The impedance perturbation is estimated using the Bayesian approach and remapped to the migrated domain by the kinematic ray tracing. Our method is demonstrated using synthetic and field data in comparison with the standard inversion. Results indicate that inversion with taking into account diffraction can improve the acoustic impedance prediction in the vicinity of local reflector discontinuities.

scholarly journals Facies Analysis and Depositoinal Environment of D-3 Reservoir Sands Vin Field, Eastern Niger Delta

2019 ◽  
pp. 1-19
Author(s):  
Onyewuchi, Chinedu Vin ◽  
Minapuye, I. Odigi
Keyword(s):  
Seismic Data ◽  
Niger Delta ◽  
Depositional Environment ◽  
Gamma Ray ◽  
Facies Analysis ◽  
Depositional Environments ◽  
Width Ratio ◽  
Neutron Density ◽  
Wireline Logs ◽  
Isopach Map

Facies analysis and depositional environment identification of the Vin field was evaluated through the integration and comparison of results from wireline logs, core analysis, seismic data, ditch cutting samples and petrophysical parameters. Well log suites from 22 wells comprising gamma ray, resistivity, neutron, density, seismic data, and ditch cutting samples were obtained and analyzed. Prediction of depositional environment was made through the usage of wireline log shapes of facies combined with result from cores and ditch cuttings sample description. The aims of this study were to identify the facies and depositional environments of the D-3 reservoir sand in the Vin field. Two sets of correlations were made on the E-W trend to validate the reservoir top and base while the isopach map was used to establish the reservoir continuity. Facies analysis was carried out to identify the various depositional environments. The result showed that the reservoir is an elongate , four way dip closed roll over anticline associated with an E-W trending growth fault and contains two structural high separated by a saddle. The offshore bar unit is an elongate sand body with length: width ratio of >3:1 and is aligned parallel to the coast-line. Analysis of the gamma ray logs indicated that four log facies were recognized in all the wells used for the study. These include: Funnel-shaped (coarsening upward sequences), bell-shaped or fining upward sequences, the bow shape and irregular shape. Based on these categories of facies, the depositional environments were interpreted as deltaic distributaries, regressive barrier bars, reworked offshore bars and shallow marine. Analysis of the wireline logs and their core/ditch cuttings description has led to the conclusion that the reservoir sandstones of the Agbada Formation in the Vin field of the eastern Niger Delta is predominantly marine deltaic sequence, strongly influenced by clastic output from the Niger Delta. Deposition occurred in a variety of littoral and neritic environment ranging from barrier sand complex to fully marine outer shelf mudstones.

scholarly journals Stratigraphy and Depositional Environment of Mauddud Formation in Ratawi Oil wells of Southern Iraq

2021 ◽  
Vol 877 (1) ◽  
pp. 012030
Author(s):  
Maha Razaq Manhi ◽  
Hamid Ali Ahmed Alsultani
Keyword(s):  
Deep Sea ◽  
Lower Cretaceous ◽  
Depositional Environment ◽  
Carbonate Platform ◽  
Depositional Environments ◽  
Oil Wells ◽  
Oil Field ◽  
Microfacies Analysis ◽  
Thin Sections ◽  
Southern Iraq

Abstract The Mauddud Formation is Iraq’s most significant and widely distributed Lower Cretaceous formation. This Formation has been investigated at a well-23 and a well-6 within Ratawi oil field southern Iraq. In this work, 75 thin sections were produced and examined. The Mauddud Formation was deposited in a variety of environments within the carbonate platform. According to microfacies analysis studying of the Mauddud Formation contains of twelve microfacies, this microfacies Mudstone to wackestone microfacies, bioclastic mudstone to wackestone microfacies, Miliolids wackestone microfacies,Orbitolina wackestone microfacies, Bioclastic wackestone microfacies, Orbitolina packstone microfacies, Peloidal packstone microfacies, Bioclastic packstone microfacies, Peloidal to Bioclastic packstone microfacies, Bioclastic grainstone microfacies, Peloidal grainstone microfacies, Rudstone microfacies. Deep sea, Shallow open marine, Restricted, Rudist Biostrome, Mid – Ramp, and Shoals are the six depositional environments in the Mauddud Formation based on these microfacies.

Evaluating the well integrity of old exploration wells as a risk factor for future storage projects – an example from the Troll field in the Norwegian North Sea

2021 ◽  
Author(s):  
Bastien Dupuy ◽  
Benjamin Emmel ◽  
Simone Zonetti
Keyword(s):  
North Sea ◽  
Early Stage ◽  
Numerical Models ◽  
Low Frequency ◽  
Oil Field ◽  
Finite Element Software ◽  
Well Completion ◽  
Well Integrity ◽  
Volumetric Assessment ◽  
Work Done

<p>More than 750 wildcat wells have been drilled in the Norwegian North Sea since 1966. Some of these wells could pose a risk for the environment, climate, and future H<sub>2</sub> and CO<sub>2</sub> storage projects by being preferred leakage paths for subsurface- and stored- gases (e.g., CH<sub>4</sub>, CO<sub>2 </sub>and/or H<sub>2</sub>). To ensure well integrity, these wells were secured by cement framing the well casing, and by building cement plugs at crucial positions in the well path before abandoning the well. However, in an early stage of exploration the geology of the subsurface was relatively uncertain, and the requirements for plug placing and how to abandon a well were not established and regulated. We analysed data relevant for the quality of a Plugging and Abandonment (P&A) work done on old exploration wells (1979 to 2003) from the Troll gas and oil field in the Norwegian North Sea. The data were extracted from public available well completion reports and the webpage of the Norwegian Petroleum Directorate. The dataset was analysed regarding their availability, plausibility and evaluated towards the present P&A regulations and geological knowledge for offshore Norway. Based on 12 criteria including reporting to the authorities, volumetric assessment of used cement quantities, position and length of the plugs in relation to reservoir- cap-rocks petrophysical conditions, and verification of the cementing job, a final P&A ranking of 31 exploration wells was established.</p><p>Parts of this data were used to build realistic numerical models of P&A'ed well to simulate electromagnetic responses using the finite element software COMSOL Multiphysics. Taking advantage of a dedicated implementation of low frequency ElectroMagnetics (EM), including effective formulations for thin electrical layers, it was possible to study the response of well components to external EM fields, both for the purpose of well detection and well monitoring. Results from the numerical models can be used as benchmark models in a realistic field scale well integrity monitoring approach.</p><p>In our presentation we will show results from the TOPHOLE project including realistic field distributions for different representative well configurations, examples of well detection and monitoring signals, and the ranking evaluation results.</p><p>Acknowledgments: This work is performed with support from the Research Council of Norway (TOPHOLE project Petromaks2-KPN 295132) and the NCCS Centre (NFR project number 257579/E20).</p>

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