Interpretation of geologic facies in seismic volume using key rock elastic properties and high-definition facies templates

2017 ◽  
Vol 5 (2) ◽  
pp. SE11-SE27 ◽  
Author(s):  
Mahbub Alam ◽  
Sabita Makoon-Singh ◽  
Joan Embleton ◽  
David Gray ◽  
Larry Lines
Keyword(s):  
Elastic Properties ◽  
Oil Recovery ◽  
Seismic Data ◽  
Effective Porosity ◽  
Rock Properties ◽  
Small Scale ◽  
High Definition ◽  
Reservoir Properties ◽  
Particle Volume ◽  
Reservoir Architecture

We have developed a deterministic workflow in mapping the small-scale (centimeter level) subseismic geologic facies and reservoir properties from conventional poststack seismic data. The workflow integrated multiscale (micrometer to kilometer level) data to estimate rock properties such as porosity, permeability, and grain size from the core data; effective porosity, resistivity, and fluid saturations using petrophysical analyses from the log data; and rock elastic properties from the log and poststack seismic data. Rock properties, such as incompressibility (lambda), rigidity (mu), and density (rho) are linked to the fine-particle-volume (FPV) ranges of different facies templates. High-definition facies templates were used in building the high-resolution (centimeter level) near-wellbore images. Facies distribution and reservoir properties between the wells were extracted and mapped from the FPV data volume built from the poststack seismic volume. Our study focused on the heavy oil-bearing Cretaceous McMurray Formation in northern Alberta. The internal reservoir architecture, such as the stacked channel bars, inclined heterolithic strata, and shale plugs, is intricate due to reservoir heterogeneity. Drilling success or optimum oil recovery will depend on whether the reservoir model accurately describes this heterogeneity. Thus, it is very important to properly identify the distribution of the permeability barriers and shale plugs in the reservoir zone. Dense vertical well control and dozens of horizontal well pairs over the area of investigation confirm a very good correlation of the geologic facies interpreted between the wells from the seismic volume.

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

2015 ◽  
Vol 3 (3) ◽  
pp. T155-T167 ◽  
Author(s):  
Debotyam Maity ◽  
Fred Aminzadeh
Keyword(s):  
Elastic Properties ◽  
Fracture Zone ◽  
Seismic Data ◽  
Integrated Approach ◽  
Temporal Analysis ◽  
Microseismic Monitoring ◽  
Well Logs ◽  
Reservoir Properties ◽  
Velocity Models ◽  
Microseismic Data

We have characterized a promising geothermal prospect using an integrated approach involving microseismic monitoring data, well logs, and 3D surface seismic data. We have used seismic as well as microseismic data along with well logs to better predict the reservoir properties to try and analyze the reservoir for improved mapping of natural and induced fractures. We used microseismic-derived velocity models for geomechanical modeling and combined these geomechanical attributes with seismic and log-derived attributes for improved fracture characterization of an unconventional reservoir. We have developed a workflow to integrate these data to generate rock property estimates and identification of fracture zones within the reservoir. Specifically, we introduce a new “meta-attribute” that we call the hybrid-fracture zone-identifier attribute (FZI). The FZI makes use of elastic properties derived from microseismic as well as log-derived properties within an artificial neural network framework. Temporal analysis of microseismic data can help us understand the changes in the elastic properties with reservoir development. We demonstrate the value of using passive seismic data as a fracture zone identification tool despite issues with data quality.

Prediction of Reservoir Properties from Seismic Data by Multivariate Geostatistics Analysis

2021 ◽  
Author(s):  
Vladimir V. Bezkhodarnov ◽  
Tatiana I. Chichinina ◽  
Mikhail O. Korovin ◽  
Valeriy V. Trushkin
Keyword(s):  
Seismic Data ◽  
Quantitative Estimation ◽  
Clay Content ◽  
Seismic Attributes ◽  
Information Value ◽  
Seismic Exploration ◽  
Rock Properties ◽  
Regression Equations ◽  
Reservoir Properties ◽  
Multivariate Geostatistics

Abstract A new technique has been developed and is being improved, which allows, on the basis of probabilistic and statistical analysis of seismic data, to predict and evaluate the most important parameters of rock properties (including the reservoir properties such as porosity and permeability), that is, oil saturation, effective thicknesses of reservoirs, their sand content, clay content of seals, and others; it is designed to predict the reservoir properties with sufficient accuracy and detail, for subsequent consideration of these estimates when evaluating hydrocarbon reserves and justifying projects for the deposits development. Quantitative reservoir-property prediction is carried out in the following stages: –Optimization of the graph ("scenario") of seismic data processing to solve not only the traditional structural problem of seismic exploration, but also the parametric one that is, the quantitative estimation of rock properties.–Computation of seismic attributes, including exclusive ones, not provided for in existing interpretation software packages.–Estimation of reservoir properties from well logs as the base data.–Multivariate correlation and regression analysis (MCRA) includes the following two stages: Establishing correlations of seismic attributes with estimates of rock properties obtained from well logs.Construction of multidimensional (multiple) regression equations with an assessment of the "information value" of seismic attributes and the reliability of the resulting predictive equations. (By the "informative value" we mean the informativeness quality of the attribute.)–Computation and construction of the forecast map variants, their analysis and producing the resultant map (as the most optimal map version) for each predicted parameter.–Obtaining the resultant forecast maps with their zoning according to the degree of the forecast reliability. The MCRA technique is tested by production and prospecting trusts during exploration and reserves’ estimation of several dozen fields in Western Siberia: Kulginskoye, Shirotnoye, Yuzhno-Tambaevskoye, etc. (Tomsk Geophysical Trust, 1997-2002); Dvurechenskoe, Zapadno-Moiseevskoe, Talovoe, Krapivinskoe, Ontonigayskoe, etc. (TomskNIPIneft, 2002–2013).

scholarly journals Estimation of reservoir properties from seismic data by smooth neural networks

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1969-1983 ◽  
Author(s):  
M. M. Saggaf ◽  
M. Nafi Toksöz ◽  
H. M. Mustafa
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Back Propagation ◽  
Reservoir Rock ◽  
Seismic Survey ◽  
Rock Properties ◽  
Reservoir Properties ◽  
Network Parameters ◽  
Generalization Problem ◽  
Validation Tests

The performance of traditional back‐propagation networks for reservoir characterization in production settings has been inconsistent due to their nonmonotonous generalization, which necessitates extensive tweaking of their parameters in order to achieve satisfactory results and avoid overfitting the data. This makes the accuracy of these networks sensitive to the selection of the network parameters. We present an approach to estimate the reservoir rock properties from seismic data through the use of regularized back propagation networks that have inherent smoothness characteristics. This approach alleviates the nonmonotonous generalization problem associated with traditional networks and helps to avoid overfitting the data. We apply the approach to a 3D seismic survey in the Shedgum area of Ghawar field, Saudi Arabia, to estimate the reservoir porosity distribution of the Arab‐D zone, and we contrast the accuracy of our approach with that of traditional back‐propagation networks through cross‐validation tests. The results of these tests indicate that the accuracy of our approach remains consistent as the network parameters are varied, whereas that of the traditional network deteriorates as soon as deviations from the optimal parameters occur. The approach we present thus leads to more robust estimates of the reservoir properties and requires little or no tweaking of the network parameters to achieve optimal results.

Reservoir properties prediction integrating controlled-source electromagnetic, prestack seismic, and well-log data using a rock-physics framework: Case study in the Hoop Area, Barents Sea, Norway

2017 ◽  
Vol 5 (2) ◽  
pp. SE43-SE60 ◽  
Author(s):  
Pedro Alvarez ◽  
Amanda Alvarez ◽  
Lucy MacGregor ◽  
Francisco Bolivar ◽  
Robert Keirstead ◽  
...  
Keyword(s):  
Seismic Data ◽  
Barents Sea ◽  
Rock Physics ◽  
Positive Outcome ◽  
Rock Properties ◽  
Integrated Analysis ◽  
Reservoir Properties ◽  
Data Set ◽  
Controlled Source ◽  
Rotation Scheme

We have developed an example from the Hoop Area of the Barents Sea showing a sequential quantitative integration approach to integrate seismic and controlled-source electromagnetic (CSEM) attributes using a rock-physics framework. The example illustrates a workflow to address the challenges of multiphysics and multiscale data integration for reservoir characterization purposes. A data set consisting of 2D GeoStreamer seismic and towed streamer electromagnetic data that were acquired concurrently in 2015 by PGS provide the surface geophysical measurements that we used. Two wells in the area — Wisting Central (7324/8-1) and Wisting Alternative (7324/7-1S) — provide calibration for the rock-physics modeling and the quantitative integrated analysis. In the first stage of the analysis, we invert prestack seismic and CSEM data separately for impedance and anisotropic resistivity, respectively. We then apply the multi-attribute rotation scheme (MARS) to estimate rock properties from seismic data. This analysis verified that the seismic data alone cannot distinguish between commercial and noncommercial hydrocarbon saturation. Therefore, in the final stage of the analysis, we invert the seismic and CSEM-derived properties within a rock-physics framework. The inclusion of the CSEM-derived resistivity information within the inversion approach allows for the separation of these two possible scenarios. Results reveal excellent correlation with known well outcomes. The integration of seismic, CSEM, and well data predicts very high hydrocarbon saturations at Wisting Central and no significant saturation at Wisting Alternative, consistent with the findings of each well. Two further wells were drilled in the area and used as blind tests in this case: The slightly lower saturation predicted at Hanssen (7324/7-2) is related to 3D effects in the CSEM data, but the positive outcome of the well is correctly predicted. At Bjaaland (7324/8-2), although the seismic indications are good, the integrated interpretation result predicts correctly that this well was unsuccessful.

Seismic attributes and kinematic azimuthal analysis for fracture and stress detection in complex geologic settings

2014 ◽  
Vol 2 (1) ◽  
pp. SA67-SA75 ◽  
Author(s):  
Krzysztof (Kris) Sliz ◽  
Saleh Al-Dossary
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
Small Scale ◽  
Seismic Velocities ◽  
Stress Detection ◽  
Fracture Detection ◽  
Reservoir Properties ◽  
Horizontal Drilling ◽  
Compressional Stress ◽  
Orientation Density

Fractured rocks can exhibit good reservoir properties and provide high-permeability passages for hydrocarbons. Understanding fracture and stress systems is a key element in successful horizontal drilling and fracking for unconventional reservoir exploration. As a result, there is growing interest in methods that can estimate fracture orientation, density, and style. However, fracture detection using surface seismic data is challenging, and the results are usually ambiguous. Each method has its own strengths and weaknesses and responds to fractures and compressional stress in different ways. A major uncertainty in fracture analysis based on azimuthally variant seismic velocities is caused by interference from structural effects, localized small-scale velocity anomalies, and directional stress. They can induce azimuthal variation in velocity, which can mask the influence on traveltimes caused by the fractures. To overcome these challenges, we focused on a fracture and compressional stress detection methodology using 3D scanning of azimuthally dependent residual moveout volumes constrained by fracture-sensitive seismic attributes. Our workflow was successfully applied to wide-azimuth, highfold land seismic data acquired over a fractured formation in the northern part of Saudi Arabia, where we were able to map 3D zones with a high probability of fractures and differentiate them from areas with higher compressional stress.

Understanding Reservoir Architectures and Steam-Chamber Growth at Christina Lake, Alberta, by Using 4D Seismic and Crosswell Seismic Imaging

2007 ◽  
Vol 10 (05) ◽  
pp. 446-452 ◽  
Author(s):  
Weimin Zhang ◽  
Sung Youn ◽  
Quang T. Doan
Keyword(s):  
Oil Recovery ◽  
Seismic Data ◽  
Lateral Spread ◽  
Test Facility ◽  
Gravity Drainage ◽  
Baseline Survey ◽  
Reservoir Heterogeneity ◽  
Fort Mcmurray ◽  
Steam Chamber ◽  
Reservoir Architecture

Summary EnCana Corporation's Christina Lake Thermal Pilot Project located 170 km south of Fort McMurray, Alberta, Canada, uses steam-assisted gravity drainage (SAGD) technology to recover bitumen from the Lower Cretaceous McMurray formation. This paper presents an analysis of time-lapse and crosswell seismic data, as part of an overall study integrating different disciplines and technologies, to understand the effects of geology on SAGD-process performance in the pilot area. A 3D baseline survey was conducted at the start of the pilot in 2001, and two follow up surveys were conducted in 2004 and 2005. In addition, six crosswell seismic profiles were acquired by placing both sources and receivers in the vertical wellbores. The goal of the seismic surveys was to better understand steam-chamber growth and reservoir architecture by detecting lithology changes, including the occurrence and distribution of mudstone stringers. Data from the surveys, especially from the crosswell profiles, indicated significant reservoir heterogeneity, and helped to characterize reservoir architecture in the pilot area more accurately. Analysis of seismic data (both 4D and crosswell) showed steam-chamber growth and oil recovery to be influenced strongly by reservoir geology. Steam-chamber growth is especially affected by the presence of low-permeability facies in the vicinity of the SAGD well pairs. Our analysis indicates that these reservoir heterogeneities have contributed to the creation of areas within the reservoir that have been unaffected by steaming operations to date. These findings are in agreement with flow-simulation results and collectively contribute significantly to the planning of future developments. Introduction The SAGD process was developed conceptually and investigated experimentally by Butler (1994). Main features of the original SAGD model for the lateral spread of the steam chamber included thermal conduction ahead of a steady-moving steam-chamber interface; countercurrent gravity drainage of mobilized bitumen, or heavy oil; and vertical rise of the steam chamber. This recovery process was field tested at the Underground Test Facility (UTF) near Fort McMurray through a number of different phases of pilot operation (Edmunds et al. 1989; Komery et al. 1993). Field applications of the SAGD process have revealed several issues of considerable importance to the recovery performance, including wellbore hydraulics, reservoir heterogeneity, effects of solution gas, and production of solids (Edmunds and Gittins 1993; Ito and Suzuki 1999; Suggett et al. 2000; Ito 1999; Edmunds 1999; Birrell 2003). This paper relates initial efforts undertaken by the Christina Lake Project team to integrate geology, geophysics (specifically, seismic technology), and reservoir engineering to further the understanding of steam-chamber growth in the McMurray reservoir for the Christina Lake SAGD project. Phase 1 of the SAGD pilot was implemented in 2001 at Christina Lake with the drilling and completion of three SAGD well pairs (A1, A2, and A3). Since then, three additional well pairs have been added (A4 well pair in October 2003 and A5 and A6 well pairs in August 2004). Fig. 1 illustrates the project area (TWP 76, R06 west of 4th Meridian), which now includes six SAGD well pairs along with observation wells and disposal wells. The following discussion will be limited to A1 through A4 well pairs, as production histories for the A5 and A6 well pairs are rather limited.

Shell's integrated quantitative interpretation workflow

2011 ◽  
Vol 51 (2) ◽  
pp. 681
Author(s):  
Frank Glass ◽  
Stephan Gelinsky ◽  
Irene Espejo ◽  
Teresa Santana ◽  
Gareth Yardley
Keyword(s):  
Seismic Data ◽  
Rock Properties ◽  
Well Log ◽  
Reservoir Properties ◽  
North West ◽  
The North ◽  
Fluid Properties ◽  
Well Data ◽  
Acoustic Responses ◽  
Carnarvon Basin

Shell Development Australia is a major asset holder in the Browse Basin and the Carnarvon Basin in the North West Shelf of Australia. In 2007, Shell Development Australia embarked on an integrated quantitative seismic interpretation project related to the Triassic Mungaroo Formation in the Carnarvon Basin. The main objective was to constrain the uncertainties in using seismic data as a predictor for rock and fluid properties of fields and prospects in the basin. This project followed a workflow that has been proven in other basins around the world, whereby the vertical and lateral variability of rock properties of both reservoir and non-reservoir lithologies are captured in general trends. The calculated trends are based on well log extractions of end member lithologies and the input of petrographic information and forward modelling. In combination with a regionally consistent 3D burial model for the estimation of remaining porosity, these established rock trends then allow for a prediction of various acoustic responses of reservoir and pore fill properties. The comparisons between the pre-drill predicted rock properties and the properties encountered after drilling at different reservoir levels have lead to a general confidence that the reservoir properties can be derived from seismic data where well data are not abundant. This increased confidence will play a major part in Shell’s attitude towards appraisal activities and decisions on various development options.

Synthetic core from conventional logs: A new method of interpretation for identification of key reservoir properties

2015 ◽  
Vol 3 (1) ◽  
pp. SA1-SA14 ◽  
Author(s):  
Mahbub Alam ◽  
Latif Ibna-Hamid ◽  
Joan Embleton ◽  
Larry Lines
Keyword(s):  
Reservoir Simulation ◽  
Reservoir Characterization ◽  
Gamma Ray ◽  
Laboratory Data ◽  
Sedimentary Facies ◽  
Rock Properties ◽  
Reservoir Properties ◽  
Particle Volume ◽  
Single Curve ◽  
Conventional Logs

We developed a unique method to generate reservoir attributes by creating an artificial core for those wells that have no core, but that have gamma, neutron, and density logs. We examined sedimentary facies distributions, reservoir attributes, and mechanical parameters of the rock for noncored wells to increase the data density and improve the understanding of the reservoir. This method eventually helps to improve high-resolution 3D geocellular models, geomechanical models, and reservoir simulation in reservoir characterization. Artificial or synthetic cores are created using a single curve that builds facies templates using the information from the cores of nearby offset wells, which belong to the same depositional environment. The single curve, called the fine particle volume (FPV), is the average of two shale volumes calculated from the gamma-ray log and from a combination of neutron and density logs. Using facies templates, the FPV curve builds the synthetic core for geocellular modeling and reservoir simulation, and it represents the sedimentary facies distribution in the well with all the reservoir attributes obtained from laboratory data of the original core. The vertical succession of the synthetic core has the characteristics of actual sedimentary facies with reservoir attributes such as porosity, permeability, and other rock properties. The result of creating the synthetic core was validated visually and statistically with the actual cores, and each of the cored wells was considered as a noncored well. The limitation of this method is associated with the accuracy of the logging data acquisition, normalization factors, and facies template selection criteria.

Interwell Tracer Tests To Optimize Operating Conditions for a Surfactant Field Trial: Design, Evaluation, and Implications

2012 ◽  
Vol 15 (02) ◽  
pp. 229-242 ◽  
Author(s):  
Hao Cheng ◽  
G. Michael Shook ◽  
Malik Taimur ◽  
Varadarajan Dwarakanath ◽  
Bruce R. Smith
Keyword(s):  
Oil Recovery ◽  
Field Trial ◽  
Tracer Tests ◽  
Tracer Test ◽  
Operating Conditions ◽  
Small Scale ◽  
Hydraulic Control ◽  
Sweep Efficiency ◽  
Reservoir Properties ◽  
Swept Volume

Summary Enhanced oil recovery (EOR) by surfactant flooding is the key to unlocking the next billion barrels of oil for Minas, one of the world's largest waterflood fields. An interwell tracer test (ITT-1) was performed before a surfactant field trial (SFT) to ensure well injectivity, demonstrate pattern confinement, quantitatively describe interwell connectivity and sweep efficiency, and provide sufficient data for reservoir evaluation. The tracer test was designed by numerical simulation. The test started in November 2009 and was terminated in February 2010. Analytical interpretation based on moment analysis and numerical reservoir simulations was conducted to evaluate ITT-1 results. Interpretation of the test results indicated various operational and reservoir properties that would have likely led to failure of the surfactant pilot. Hydraulic control of the SFT pattern was not achieved; in fact, less than 20% of one tracer was recovered. Many small-scale heterogeneities were identified that led to a lower-than-expected reservoir volume contacted. Unexpected communication between the target sand and the underlying sands outside the pattern also contributed to low tracer recovery and low swept volume. The tracer test was history matched, and additional features were incorporated in the reservoir model, and a new tracer design (ITT-2) was optimized to correct low sweep efficiency and poor hydraulic control. New information from ITT-2 will be used to further optimize operating conditions for SFTs. Failure to conduct the tracer tests would have likely revealed these unfavorable reservoir and operational conditions during the SFT. Had oil recovery been poor (because of low swept volume), it would have erroneously been attributed to a poor SFT rather than to the true causes. ITT-1 is considered successful because it allowed us to redesign injection/hydraulic control during the relatively inexpensive tracer test and thus evaluate the surfactant trial without bias.

scholarly journals Reservoir characterisation using process-response simulations: the Lower Cretaceous Rijn Field, West Netherlands Basin

2003 ◽  
Vol 82 (4) ◽  
pp. 313-324
Author(s):  
L.J.H. Alberts ◽  
C.R. Geel ◽  
J.J. Klasen
Keyword(s):  
Seismic Data ◽  
Lower Cretaceous ◽  
Small Scale ◽  
Depositional Model ◽  
Response Model ◽  
Reservoir Properties ◽  
Reservoir Heterogeneity ◽  
Geological Processes ◽  
Basin Scale ◽  
Well Data

AbstractPetroleum geologists always need to deal with large gaps in data resolution and coverage during reservoir characterisation. Seismic data show only large geological structures, whereas small-scale structures and reservoir properties can be observed only at well locations. In the area between wells, these properties are often estimated by means of geostatistics. Numerical simulation of sedimentary processes offers an alternative method to predict these properties and can improve the understanding of the controls on reservoir heterogeneity. Although this kind of modelling is widely used on basin scale in exploration geology, its application on field scale in production geology is virtually non-existent. We have assessed whether the recent developments in numerical modelling can also aid petroleum geologists in the interpretation of the reservoir geology.Seismic data, well data and a process-response model for coastal environments were used to characterise the Lower Cretaceous oil-bearing Rijn Field. Interpretation of seismic and well data led to a definition of the structural setting and the depositional model of the Rijn Member in the area. From the sedimentological interpretation the sea-level history could be estimated, which is the one of the most important input parameters for the process-response model.Application of the process-response simulator to the Rijn Field resulted in approval of the depositional model. The output was presented in a 2-dimensional north-south profile, which corresponds very well to the well logs along this section. The results demonstrate that numerical simulations of geological processes can be very useful as a tool to explore many likely geological scenarios. While it cannot be used to supply a unique solution in many cases, it forms a helpful guide during reservoir characterisation to find an optimal scenario of the controls on deposition of the Rijn Member, which contributes to the understanding of the inter-well reservoir heterogeneity.

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