Well log and seismic data analysis for complex pore-structure carbonate reservoir using 3D rock physics templates

2018 ◽  
Vol 151 ◽  
pp. 175-183 ◽  
Author(s):  
Hongbing Li ◽  
Jiajia Zhang
Keyword(s):  
Data Analysis ◽  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Well Log

Porosity estimation based on rock skeleton general formula and comprehensive pore structure parameter – An application to a tight-sand reservoir

2021 ◽  
pp. 1-59
Author(s):  
Kai Lin ◽  
Xilei He ◽  
Bo Zhang ◽  
Xiaotao Wen ◽  
Zhenhua He ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Structure Parameters ◽  
Pore Structure Parameter ◽  
Elastic Parameters ◽  
Physics Model ◽  
Rock Physics Model ◽  
Porosity Estimation

Most of current 3D reservoir’s porosity estimation methods are based on analyzing the elastic parameters inverted from seismic data. It is well-known that elastic parameters vary with pore structure parameters such as pore aspect ratio, consolidate coefficient, critical porosity, etc. Thus, we may obtain inaccurate 3D porosity estimation if the chosen rock physics model fails properly address the effects of pore structure parameters on the elastic parameters. However, most of current rock physics models only consider one pore structure parameter such as pore aspect ratio or consolidation coefficient. To consider the effect of multiple pore structure parameters on the elastic parameters, we propose a comprehensive pore structure (CPS) parameter set that is generalized from the current popular rock physics models. The new CPS set is based on the first order approximation of current rock physics models that consider the effect of pore aspect ratio on elastic parameters. The new CPS set can accurately simulate the behavior of current rock physics models that consider the effect of pore structure parameters on elastic parameters. To demonstrate the effectiveness of proposed parameters in porosity estimation, we use a theoretical model to demonstrate that the proposed CPS parameter set properly addresses the effect of pore aspect ratio on elastic parameters such as velocity and porosity. Then, we obtain a 3D porosity estimation for a tight sand reservoir by applying it seismic data. We also predict the porosity of the tight sand reservoir by using neural network algorithm and a rock physics model that is commonly used in porosity estimation. The comparison demonstrates that predicted porosity has higher correlation with the porosity logs at the blind well locations.

The role of EM rock physics and seismic data in integrated 3D CSEM data analysis

2009 ◽  
Author(s):  
I. Brevik ◽  
Pål T. Gabrielsen ◽  
Jan Petter Morten
Keyword(s):  
Data Analysis ◽  
Seismic Data ◽  
Rock Physics

Seismic reservoir characterization of the Bone Spring and Wolfcamp Formations in the Delaware Basin: Challenges and uncertainty in characterization using rock physics — A case study: Part 2

2020 ◽  
Vol 8 (4) ◽  
pp. T1057-T1069
Author(s):  
Ritesh Kumar Sharma ◽  
Satinder Chopra ◽  
Larry Lines
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Well Log ◽  
Data Set ◽  
Frequency Model ◽  
Log Data ◽  
Delaware Basin ◽  
Seismic Reservoir

The discrimination of fluid content and lithology in a reservoir is important because it has a bearing on reservoir development and its management. Among other things, rock-physics analysis is usually carried out to distinguish between the lithology and fluid components of a reservoir by way of estimating the volume of clay, water saturation, and porosity using seismic data. Although these rock-physics parameters are easy to compute for conventional plays, there are many uncertainties in their estimation for unconventional plays, especially where multiple zones need to be characterized simultaneously. We have evaluated such uncertainties with reference to a data set from the Delaware Basin where the Bone Spring, Wolfcamp, Barnett, and Mississippian Formations are the prospective zones. Attempts at seismic reservoir characterization of these formations have been developed in Part 1 of this paper, where the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, accounting for the temporal and lateral variation in the seismic wavelets, and building of robust low-frequency model for prestack simultaneous impedance inversion were determined. We determine the challenges and the uncertainty in the characterization of the Bone Spring, Wolfcamp, Barnett, and Mississippian sections and explain how we overcame those. In the light of these uncertainties, we decide that any deterministic approach for characterization of the target formations of interest may not be appropriate and we build a case for adopting a robust statistical approach. Making use of neutron porosity and density porosity well-log data in the formations of interest, we determine how the type of shale, volume of shale, effective porosity, and lithoclassification can be carried out. Using the available log data, multimineral analysis was also carried out using a nonlinear optimization approach, which lent support to our facies classification. We then extend this exercise to derived seismic attributes for determination of the lithofacies volumes and their probabilities, together with their correlations with the facies information derived from mud log data.

Geophysical pore type inversion in carbonate reservoir: integration of cores, well-logs, and seismic data (Yadana field, offshore Myanmar)

Geophysics ◽  
2021 ◽  
pp. 1-69
Author(s):  
Thomas Teillet ◽  
François Fournier ◽  
Luanxiao Zhao ◽  
Jean Borgomano ◽  
Fei Hong
Keyword(s):  
Seismic Data ◽  
Effective Medium Theory ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Well Logs ◽  
Inversion Method ◽  
Gas Field ◽  
Medium Theory ◽  
Scale Thickness ◽  
Pore Types

Detection of pore types and diagenetic features from seismic data is a major challenge for the evaluation of carbonate reservoirs in the subsurface. Based on a detailed petrographical and petrophysical analysis of carbonate rock using optical and scanning electron microscopy, mercury-injection measurements, digital image analysis, and well logs, we have determined the potential of the geophysical pore type (αP) inversion a rock physics inversion scheme based on the differential effective medium theory – to quantitatively and qualitatively characterize the pore type distribution from acoustic data in the Yadana carbonate gas field (Early Miocene, offshore Myanmar). The geophysical pore type (αP) is revealed to be an upscalable parameter, whose depositional/diagenetic interpretation may be performed at well log and at seismic scales. We apply the inversion method on a 3D seismic data to map the reservoir-scale distribution and highlight the occurrence of laterally extended (100–1000 m) subseismic- to seismic-scale (thickness >5 m) geologic bodies. From this approach, two main reservoir geobodies are discriminated and interpreted in terms of depositional and diagenetic fabrics: (1) highly microporous, decameter-scale reservoir units (approximately 80% of the reservoir), mainly consisting of foraminiferal, red algae floatstone to rudstone with vuggy, moldic porosity, and characterized by moderate to high αP (0.11–0.20) and (2) thin, stratiform, cemented scleractinian floatstone/brecciated units (5–10 m; approximately 20% of the reservoir) with low microporosity and macroporosity and exhibiting low αP values (<0.11).

Prediction of deep-buried gas carbonate reservoir by combining prestack seismic-driven elastic properties with rock physics in Sichuan Basin, southwestern China

2014 ◽  
Vol 2 (4) ◽  
pp. T193-T204
Author(s):  
Jiqiang Ma ◽  
Jianhua Geng ◽  
Tonglou Guo
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Sichuan Basin ◽  
Incident Angle ◽  
Rock Physics ◽  
Carbonate Reservoir ◽  
Southwestern China ◽  
Marine Carbonate ◽  
The Sichuan Basin ◽  
Elastic Impedance

The prediction of seismic reservoirs in marine carbonate areas in the Sichuan Basin, southwestern China, is very challenging because the target zone is deeply buried (more than 6 km), with multiphase tectonic movements, complex diagenesis, and low porosity, and the incident angle of the seismic data is finite. We developed reliable hydrocarbon indicators of a marine carbonate deposit based on prestack elastic impedance (EI) and well observations. Although the hydrocarbon indicators can be calculated from elastic parameters, the inversion for EI-driven elastic attributes is usually unstable. To constrain the inversion process, we discovered a new strategy to recover the elastic properties from EIs within a Bayesian framework (called Bayesian elastic parameter inversion from elastic impedance). We applied the strategy to a carbonate reef identified at the center of a study line based on the geologic context and the seismic reflection patterns. We then used rock-physics analyses to classify the lithologies and the reservoir at a well location. Rock-physics modeling quantified the hydrocarbon sensitivity of the elastic attributes. Fluid substitution was used to investigate the effects of pore fluids on the elastic properties. A comparison of two synthetic amplitude-versus-angle responses (for gas and brine saturation) with real seismic data showed that the reservoir was gas charged. Using well-based crossplot analyses, reliable direct hydrocarbon indicators can be constructed for a deeply buried gas reservoir and were effective for interpretation in an area of marine carbonates in the Sichuan Basin.

Overseas Offshore Reservoir Quick Forecast by Sedimentary Facies

2013 ◽  
Vol 321-324 ◽  
pp. 2444-2447
Author(s):  
Cheng Hua Ou ◽  
Qiang Han ◽  
Wen Jiang Zhou
Keyword(s):  
Data Analysis ◽  
Seismic Data ◽  
Sedimentary Facies ◽  
Well Log ◽  
Forecast Method ◽  
Core Data ◽  
The Core ◽  
Offshore Oil

There are more and more overseas offshore oil project in china, along of external interdependent level in petroleum becomes upgrading year by year. Therefore, developing quick forecast method on overseas offshore reservoirs becomes very necessary. The method is divided into three steps: i the core data analysis results are used to calibrate the interpretation about logs of well, ii the well log interpreted results are used to mark seismic data, iii the abundant seismic data is used to forecast overseas offshore reservoir quickly. And rear end in this article, an overseas offshore reservoir is used to as an example to verify the applicability and reliability of the method.

Two-parameter prestack seismic inversion of porosity and pore structure parameter of fractured carbonate reservoirs: Part 1 — Methods

2018 ◽  
Vol 6 (4) ◽  
pp. SM1-SM8 ◽  
Author(s):  
Tingting Zhang ◽  
Yuefeng Sun
Keyword(s):  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Seismic Inversion ◽  
High Porosity ◽  
Structure Parameter ◽  
Pore Structure Parameter ◽  
Fractured Zones ◽  
Physics Model ◽  
Rock Physics Model

Fractured zones in deeply buried carbonate hills are important because they often have better permeability resulting in prolific production than similar low-porosity rocks. Nevertheless, their detection poses great challenge to conventional seismic inversion methods because they are mostly low in acoustic impedance and bulk modulus, hardly distinguishable from high-porosity zones or mudstones. A proxy parameter of pore structure defined in a rock-physics model, the so-called Sun model, has been used for delineating fractured zones in which the pore structure parameter is relatively high, whereas the porosity is low in general. Simultaneous seismic inversion of the pore structure parameter and porosity proves to be difficult and nontrivial in practice. Although the pore structure parameter is well-defined at locations where density, P-, and S-velocity are known from logs, estimation of P- and S-velocity information, especially density information from prestack seismic data is rather challenging. A three-step iterative inversion method, which uses acoustic, gradient, and elastic impedance from angle-stacked seismic data as input to the rock-physics model for calculating porosity and bulk and shear pore structure parameters simultaneously, is proposed and implemented to solve this problem. The methodology is successfully tested with well logs and seismic data from a deeply buried carbonate hill in the Bohai Bay Basin, China.

Mapping lithofacies and pore‐fluid probabilities in a North Sea reservoir: Seismic inversions and statistical rock physics

Geophysics ◽  
2001 ◽  
Vol 66 (4) ◽  
pp. 988-1001 ◽  
Author(s):  
T. Mukerji ◽  
A. Jørstad ◽  
P. Avseth ◽  
G. Mavko ◽  
J. R. Granli
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Probability Distributions ◽  
Rock Physics ◽  
Normal Incidence ◽  
Seismic Inversion ◽  
Training Data ◽  
Well Log ◽  
Statistical Rock Physics

Reliably predicting lithologic and saturation heterogeneities is one of the key problems in reservoir characterization. In this study, we show how statistical rock physics techniques combined with seismic information can be used to classify reservoir lithologies and pore fluids. One of the innovations was to use a seismic impedance attribute (related to the [Formula: see text] ratio) that incorporates far‐offset data, but at the same time can be practically obtained using normal incidence inversion algorithms. The methods were applied to a North Sea turbidite system. We incorporated well log measurements with calibration from core data to estimate the near‐offset and far‐offset reflectivity and impedance attributes. Multivariate probability distributions were estimated from the data to identify the attribute clusters and their separability for different facies and fluid saturations. A training data was set up using Monte Carlo simulations based on the well log—derived probability distributions. Fluid substitution by Gassmann’s equation was used to extend the training data, thus accounting for pore fluid conditions not encountered in the well. Seismic inversion of near‐offset and far‐offset stacks gave us two 3‐D cubes of impedance attributes in the interwell region. The near‐offset stack approximates a zero‐offset section, giving an estimate of the normal incidence acoustic impedance. The far offset stack gives an estimate of a [Formula: see text]‐related elastic impedance attribute that is equivalent to the acoustic impedance for non‐normal incidence. These impedance attributes obtained from seismic inversion were then used with the training probability distribution functions to predict the probability of occurrence of the different lithofacies in the interwell region. Statistical classification techniques, as well as geostatistical indicator simulations were applied on the 3‐D seismic data cube. A Markov‐Bayes technique was used to update the probabilities obtained from the seismic data by taking into account the spatial correlation as estimated from the facies indicator variograms. The final results are spatial 3‐D maps of not only the most likely facies and pore fluids, but also their occurrence probabilities. A key ingredient in this study was the exploitation of physically based seismic‐to‐reservoir property transforms optimally combined with statistical techniques.

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