Estimation of pulse shaping for well logs

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1605-1611 ◽  
Author(s):  
K. Sølna
Keyword(s):  
Stochastic Model ◽  
Pulse Shaping ◽  
Well Logs ◽  
Well Log ◽  
Smoothing Effect ◽  
Sonic Log ◽  
Apparent Attenuation ◽  
Sonic Logs ◽  
Real Medium

A wavelet propagating in a finely layered lossless medium is subject to apparent attenuation that changes its shape. Can a sonic log be used to characterize this change? I show that numerical simulations with the well‐log as medium give an apparent attenuation or diffusion of the pulse that is very different from the attenuation in the real medium. This is due to the smoothing effect of the well‐log tool. Based on a version of the O’Doherty‐Anstey approximation, I derive an expression that reveals the role of the tool. Using a sonic log, I verify the theory and show how tool effects can be mitigated by deconvolution. I also propose a two‐scale stochastic model for the sonic log and a procedure for estimation of its parameters. One application of sonic logs is to quantify apparent attenuation and, in this context, my results are important.

scholarly journals Determining Fracture Pressure Gradients from Well Logs

2020 ◽  
Vol 8 (1) ◽  
pp. 5
Author(s):  
Udo K. I ◽  
George N. J ◽  
Akankpo A. O ◽  
Azuoko G. B ◽  
Aka M.U
Keyword(s):  
Niger Delta ◽  
Well Logs ◽  
Pressure Gradients ◽  
Seal Failure ◽  
Fracture Pressure ◽  
Shear Wave Velocities ◽  
Pore Pressures ◽  
Sonic Log ◽  
Drilling Operations ◽  
Sonic Logs

Fracture pressure gradient is one of the essential parameters used in determining mud weight profiles during drilling operations. We have determined fracture pressure gradients from well logs obtained from three producing wells in Onshore Niger Delta using an empirical model. Key logs needed for the prediction were conditioned and quality controlled to meet the standard required for reliable results. The true vertical stress, normal compaction trend and compressional shale velocity trends were generated from the logs (density and sonic logs). Poison’s ratio was obtained from compressional and shear wave velocities derived from sonic log. Pore pressures in the three wells were then predicted using Eaton’s Method. The predicted pore pressures, overburden pressures and poison’s ratio were used to determine fracture pressures using Ben Eaton’s Model. Results showed that there is a suitable drilling margin at all depths only in well G-005. Drilling well A-001 to a depth of 10962.81 ft and K-001 to a depth of 12626.9 ft will fracture the formations because the fluid pressures at those depths approximate the fracture pressures of 8536.7psi and 9506 psi with corresponding gradients of 0.78 psi/ft and 0.75 psi/ft respectively. The implication is that drilling deeper in the field will results in very low seal capacity magnitudes, thereby presenting a higher risk of top-seal failure.  

Stochastic discrete fracture network modeling in shale reservoirs via integration of seismic attributes and petrophysical data

2021 ◽  
pp. 1-50
Author(s):  
Yongchae Cho
Keyword(s):  
Seismic Data ◽  
Stochastic Approach ◽  
Fracture Network ◽  
Natural Fracture ◽  
Well Logs ◽  
Fracture Model ◽  
Well Log ◽  
Discrete Fracture ◽  
Discrete Fracture Network Modeling ◽  
Fracture Network Modeling

The prediction of natural fracture networks and their geomechanical properties remains a challenge for unconventional reservoir characterization. Since natural fractures are highly heterogeneous and sub-seismic scale, integrating petrophysical data (i.e., cores, well logs) with seismic data is important for building a reliable natural fracture model. Therefore, I introduce an integrated and stochastic approach for discrete fracture network modeling with field data demonstration. In the proposed method, I first perform a seismic attribute analysis to highlight the discontinuity in the seismic data. Then, I extrapolate the well log data which includes localized but high-confidence information. By using the fracture intensity model including both seismic and well logs, I build the final natural fracture model which can be used as a background model for the subsequent geomechanical analysis such as simulation of hydraulic fractures propagation. As a result, the proposed workflow combining multiscale data in a stochastic approach constructs a reliable natural fracture model. I validate the constructed fracture distribution by its good agreement with the well log data.

Integration of 3D Volumetric Computed Tomography Scan Image Data with Conventional Well Logs for Detection of Petrophysical Rock Classes

2021 ◽  
pp. 1-18
Author(s):  
Andres Gonzalez ◽  
Zoya Heidari ◽  
Olivier Lopez
Keyword(s):  
Ct Scan ◽  
Well Logs ◽  
Well Log ◽  
3D Ct ◽  
Rock Classification ◽  
Formation Evaluation ◽  
Rock Fabric ◽  
3D Ct Scan ◽  
Scan Data ◽  
Image Analysis Techniques

Summary Core measurements are used for rock classification and improved formation evaluation in both cored and noncored wells. However, the acquisition of such measurements is time-consuming, delaying rock classification efforts for weeks or months after core retrieval. On the other hand, well-log-based rock classification fails to account for rapid spatial variation of rock fabric encountered in heterogeneous and anisotropic formations due to the vertical resolution of conventional well logs. Interpretation of computed tomography (CT) scan data has been identified as an attractive and high-resolution alternative for enhancing rock texture detection, classification, and formation evaluation. Acquisition of CT scan data is accomplished shortly after core retrieval, providing high-resolution data for use in petrophysical workflows in relatively short periods of time. Typically, CT scan data are used as two-dimensional (2D) cross-sectional images, which is not suitable for quantification of three-dimensional (3D) rock fabric variation, which can increase the uncertainty in rock classification using image-based rock-fabric-related features. The methods documented in this paper aim to quantify rock-fabric-related features from whole-core 3D CT scan image stacks and slabbed whole-core photos using image analysis techniques. These quantitative features are integrated with conventional well logs and routine core analysis (RCA) data for fast and accurate detection of petrophysical rock classes. The detected rock classes are then used for improved formation evaluation. To achieve the objectives, we conducted a conventional formation evaluation. Then, we developed a workflow for preprocessing of whole-core 3D CT-scan image stacks and slabbed whole-core photos. Subsequently, we used image analysis techniques and tailor-made algorithms for the extraction of image-based rock-fabric-related features. Then, we used the image-based rock-fabric-related features for image-based rock classification. We used the detected rock classes for the development of class-based rock physics models to improve permeability estimates. Finally, we compared the detected image-based rock classes against other rock classification techniques and against image-based rock classes derived using 2D CT scan images. We applied the proposed workflow to a data set from a siliciclastic sequence with rapid spatial variations in rock fabric and pore structure. We compared the results against expert-derived lithofacies, conventional rock classification techniques, and rock classes derived using 2D CT scan images. The use of whole-core 3D CT scan image-stacks-based rock-fabric-related features accurately captured changes in the rock properties within the evaluated depth interval. Image-based rock classes derived by integration of whole-core 3D CT scan image-stacks-based and slabbed whole-core photos-based rock-fabric-related features agreed with expert-derived lithofacies. Furthermore, the use of the image-based rock classes in the formation evaluation of the evaluated depth intervals improved estimates of petrophysical properties such as permeability compared to conventional formation-based permeability estimates. A unique contribution of the proposed workflow compared to the previously documented rock classification methods is the derivation of quantitative features from whole-core 3D CT scan image stacks, which are conventionally used qualitatively. Furthermore, image-based rock-fabric-related features extracted from whole-core 3D CT scan image stacks can be used as a tool for quick assessment of recovered whole core for tasks such as locating best zones for extraction of core plugs for core analysis and flagging depth intervals showing abnormal well-log responses.

Petrophysical Type Curves for Identifying the Electrical Character of Petroleum Reservoirs

2007 ◽  
Vol 10 (06) ◽  
pp. 711-729 ◽  
Author(s):  
Paul Francis Worthington
Keyword(s):  
Water Saturation ◽  
Early Stage ◽  
Well Logs ◽  
Log Analysis ◽  
Well Log ◽  
Formation Water ◽  
Water Conductivity ◽  
Core Data ◽  
Water Saturated ◽  
Petrophysical Evaluation

Summary A user-friendly type chart has been constructed as an aid to the evaluation of water saturation from well logs. It provides a basis for the inter-reservoir comparison of electrical character in terms of adherence to, or departures from, Archie conditions in the presence of significant shaliness and/or low formation-water salinity. Therefore, it constitutes an analog facility. The deliverables include reservoir classification to guide well-log analysis, a protocol for optimizing the acquisition of special core data in support of log analysis, and reservoir characterization in terms of an (analog) porosity exponent and saturation exponent. The type chart describes a continuum of electrical behavior for both water and hydrocarbon zones. This is important because some reservoir rocks can conform to Archie conditions in the fully water-saturated state, but show pronounced departures from Archie conditions in the partially water-saturated state. In this respect, the chart is an extension of earlier approaches that were restricted to the water zone. This extension is achieved by adopting a generalized geometric factor—the ratio of water conductivity to formation conductivity—regardless of the degree of hydrocarbon saturation. The type chart relates a normalized form of this geometric factor to formation-water conductivity, a "shale" conductivity term, and (irreducible) water saturation. The chart has been validated using core data from comprehensively studied reservoirs. A workflow details the application of the type chart to core and/or log data. The analog role of the chart is illustrated for reservoir units that show different levels of non-Archie effects. The application of the method should take rock types, scale effects, the degree of core sampling, and net reservoir criteria into account. The principal benefit is a reduced uncertainty in the choice of a procedure for the petrophysical evaluation of water saturation, especially at an early stage in the appraisal/development process, when adequate characterizing data may not be available. Introduction One of the ever-present problems in petrophysics is how to carry out a meaningful evaluation of well logs in situations where characterizing information from quality-assured core analysis is either unavailable or is insufficient to satisfactorily support the log interpretation. This problem is especially pertinent at an early stage in the life of a field, when reservoir data are relatively sparse. Data shortfalls could be mitigated if there was a means of identifying petrophysical analogs of reservoir character, so that the broader experience of the hydrocarbon industry could be utilized in constructing reservoir models and thence be brought to bear on current appraisal and development decisions. Here, a principal requirement calls for type charts of petrophysical character, on which data from different reservoirs can be plotted and compared, as a basis for aligning approaches to future data acquisition and interpretation. This need manifests itself strongly in the petrophysical evaluation of water saturation, a process that traditionally uses the electrical properties of a reservoir rock to deliver key building blocks for an integrated reservoir model. The solution to this problem calls for an analog facility through which the electrical character of a subject reservoir can be compared with others that have been more comprehensively studied. In this way, the degree of confidence in log-derived water saturation might be reinforced. At the limit, the log analyst needs a reference basis for recourse to capillary pressure data in cases where the well-log evaluation of water saturation turns out to be prohibitively uncertain.

scholarly journals ACOUSTIC SEISMIC WAVE ATTENUATION IN ROCKS: ESTIMATES INSTABILITIES, FREQUENCY-DEPENDENCE AND INCOHERENCES

2017 ◽  
Vol 35 (3) ◽  
Author(s):  
Julián David Peláez ◽  
Luis Alfredo Montes
Keyword(s):  
Frequency Shift ◽  
Seismic Wave ◽  
Wave Attenuation ◽  
Spectral Ratio ◽  
Well Logs ◽  
Well Log ◽  
Seismic Profiles ◽  
Seismic Wave Attenuation ◽  
Transmission Coefficients ◽  
Centroid Frequency

ABSTRACT. Seismic wave attenuation (Q−1) values indicate relevant media properties, such as fluid content and porosity. Q−1 estimates, obtained using both VSP and conventional well log data, did not exhibit comparable trends, nor values. Whereas VSP results represent total attenuation, well log Q−1, which, theoretically, should represent scattering losses, displayed a low percentage correlation with transmission coefficients and other well logs. The influence of processing routines, chosen methodology and input parameters on Q−1-values suggests that ASR (Amplitude Spectral Ratio) and CFS (Centroid Frequency Shift) attenuation estimates should be regarded, in practical terms, as relative quantities instead of absolute ones. Seemingly incoherent negative values are frequent, nonetheless these could hold a physical meaning related to elastic amplification at interfaces. Considering that quality factor (Q) values obtained were more unstable than Q−1-values, it is advisable to report the latter. Keywords: Vertical Seismic Profiles, well logs, transmission coefficients, scattering, amplification.RESUMO. Os valores de atenuação da onda sísmica (Q−1) indicam propriedades relavantes dos meios, tais como conteúdo de fluido e porosidade. As estimativas do Q−1, obtidas usando dados de VSP e dados de poços convencionais, não apresentaram tendências nem valores comparáveis. Enquanto os resultados de VSP representamatenuação total, os resultados dos dados de poços, que teoricamente deveriam representar perdas de dispersão, apresentaramuma baixa correlação percentual com os coeficientes de transmissão e outros dados de poços. A influência das rotinas de processamento, da metodologia escolhida e dos parâmetros de entrada nos valores Q−1 sugere que as estimativas de atenuação ASR (Amplitude Spectral Ratio) e CFS (Centroid Frequency Shift) devem ser, em termos práticos, consideradas como quantidades relativas em vez de absolutas. Valores negativos aparentemente incoerentes são frequentes, no entanto estes poderiam conter um significado físico relacionado `a amplificação elástica nas interfaces. Considerando que os valores do fator de qualidade (Q) obtidos foram mais instáveis do que os valores de Q−1, é aconselhável documentar o último. Palavras-chave: Perfis Sísmicos Verticais, registros de poços, coeficientes de transmissão, dispersão, amplificação.

ROBUST SONIC LOG TRACKING USING A MULTI-RESOLUTION APPROACH

2021 ◽  
Author(s):  
Ting Lei ◽  
◽  
Michiko Hamada ◽  
Adam Donald ◽  
Takeshi Endo ◽  
...  
Keyword(s):  
Sudden Change ◽  
Processing Technique ◽  
Tracking Algorithm ◽  
Signal Loss ◽  
Tracking Accuracy ◽  
Signal Processing Technique ◽  
Waveform Data ◽  
Sonic Log ◽  
Tracking Process ◽  
Sonic Logs

Borehole acoustic logging is an acquisition method that is regarded as the most efficient and reliable method to measure subsurface rock elastic property. It plays an important role in both well construction and reservoir evaluation. The acquisition is carried out downhole by firing a transducer and then collecting waveforms at an array of receivers. A signal processing technique such as the slowness-time-coherence method is used to process array waveform data to resolve slownesses from different arrivals. To label these slowness values, a classification algorithm is then required to first determine if a primary (P) or a secondary (S) arrival exists or not, and then label out the existing ones at each depth of the entire logging interval to deliver continuous compressional and shear slowness logs. Such a process is referred as automatic sonic log tracking process. Clearly, it is of great importance to be able to track log as accurately as possible. Traditional approaches either use predefined slowness or arrival time boundary to distinguish them or treats slowness peaks in consecutive depths like “moving particles” and use a particle tracking algorithm to estimate their trace. However, such a tracking algorithm is often challenged by a sudden change in formation types at bed boundary, fine-scale heterogeneity, downhole logging noise, as well as unpredicted signal loss due to bad borehole shape or gas influx. Consequently, the tracking process is often a tricky task that requires heavy manual quality control and relabeling process, which poses significant bottleneck for a timely delivery of sonic logs for downstream petrophysical and geomechanical applications. In this paper, we propose a new physical based multi-resolution tracking algorithm that can improve the robustness of the tracking process. The new algorithm is inspired by the fact that different resolution sonic logs can sense different rock volumes and therefore response differently to a thin layer or an interval with bad borehole conditions. It works by grouping slowness-time peaks with different resolutions to form clusters, which are then tracked by the connecting with its neighboring depths. As different resolution slownesses are physically constrained by the convolution response of heterogeneous layers, the cluster-based multi-resolution tracking approach exhibits better logging depth continuity than the traditional single-resolution methods. Outliers due to noise can be confidently avoided. Finally, remaining gaps due to shoulder bed boundary can be patched by a convolution constrained optimization process from coherences from different resolutions. This new approach is therefore referred as a multi-resolution approach and can significantly improve sonic log tracking accuracy than the single resolution approach. This new algorithm has been tested on several sonic logging field data and demonstrates robust tracking performance of sonic P&S logs. Additionally, with the multi-resolution processing, sonic logs with different resolution can be reliably obtained and a high-quality high-resolution sonic log can also be automatically delivered, which can then be used to match resolution of other petrophysical logs for various types of interpretation.

scholarly journals Depositional facies model and reservoir characterization of USANI field 1, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 57 ◽  
Author(s):  
Godwin Aigbadon ◽  
A.U Okoro ◽  
Chuku Una ◽  
Ocheli Azuka
Keyword(s):  
Tidal Flat ◽  
Water Saturation ◽  
Well Logs ◽  
Physical Analysis ◽  
Well Log ◽  
Delta Front ◽  
Depositional Facies ◽  
Facies Model ◽  
Core Data ◽  
The Core

The 3-D depositional environment was built using seismic data. The depositional facies was used to locate channels with highly theif zones and distribution of various sedimentary facies. The integration core data and the gamma ray log trend from the wells within the studied interval with right boxcar/right bow-shape indicate muddy tidal flat to mixed tidal flat environments. The bell–shaped from the well logs with the core data indicate delta front with mouth bar, the blocky box- car trend from the well logs with the core data indicate tidal point bar with tidal channel fill. The integration of seismic to well log tie display a good tie in the wells across the field. The attribute map from velocity analysis revealed the presence of hydrocarbons in the identified sands (A, B, C, D1, D2, D4, D5). The major faults F1, F2, F3 and F4 with good sealing capacity are responsible for hydrocarbon accumulation in the field. Detailed petro physical analysis of well log data showed that the studied interval are characterized by sand-shale inter-beds. Eight reservoirs were mapped at depth intervals of 2886m to 3533m with their thicknesses ranging from 12m to 407m. Also the Analysis of the petrophysical results showed that porosity of the reservoirs range from 14% to 28 %; permeability range from 245.70 md to 454.7md; water saturation values from 21.65% to 54.50% and hydrocarbon saturation values from 45.50% to 78.50 %. The by-passed hydrocarbons were identified and estimated in low resistivity pay sands D1, D2 at depth of 2884m – 2940m, sand D5 at depth of 3114m – 3126m respectively. The model serve as a basis for establishing facies model in the field.

scholarly journals Instability of CII is needed for efficient switching between lytic and lysogenic development in bacteriophage 186

2020 ◽  
Vol 48 (21) ◽  
pp. 12030-12041
Author(s):  
Iain M Murchland ◽  
Alexandra Ahlgren-Berg ◽  
Julian M J Pietsch ◽  
Alejandra Isabel ◽  
Ian B Dodd ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Transcriptional Activator ◽  
Uv Treatment ◽  
Prophage Induction ◽  
In Vivo Degradation

Abstract The CII protein of temperate coliphage 186, like the unrelated CII protein of phage λ, is a transcriptional activator that primes expression of the CI immunity repressor and is critical for efficient establishment of lysogeny. 186-CII is also highly unstable, and we show that in vivo degradation is mediated by both FtsH and RseP. We investigated the role of CII instability by constructing a 186 phage encoding a protease resistant CII. The stabilised-CII phage was defective in the lysis-lysogeny decision: choosing lysogeny with close to 100% frequency after infection, and forming prophages that were defective in entering lytic development after UV treatment. While lysogenic CI concentration was unaffected by CII stabilisation, lysogenic transcription and CI expression was elevated after UV. A stochastic model of the 186 network after infection indicated that an unstable CII allowed a rapid increase in CI expression without a large overshoot of the lysogenic level, suggesting that instability enables a decisive commitment to lysogeny with a rapid attainment of sensitivity to prophage induction.

MODELLING THE ROLE OF IMMUNITY IN MACROPARASITE INFECTIONS

1995 ◽  
Vol 03 (02) ◽  
pp. 379-387 ◽  
Author(s):  
MO YANG HYUN ◽  
FRANCISCO ANTONIO BEZERRA COUTINHO ◽  
EDUARDO MASSAD
Keyword(s):  
Stochastic Model

A stochastic model is proposed to analyse the role of immunity processes in modulating the infection by macroparasites, with applications in schistosomiasis.

On: “Automated identification of rock boundaries: an application of the Walsh transform to geophysical well‐log analysis” by E. N. Lanning and D. M. Johnson (GEOPHYSICS, v. 48, p. 197–205, February, 1983).

Geophysics ◽  
1984 ◽  
Vol 49 (10) ◽  
pp. 1801-1802
Author(s):  
David S. K. Chan
Keyword(s):  
Well Logs ◽  
Walsh Transform ◽  
Log Analysis ◽  
Well Log ◽  
Transform Domain ◽  
Original Signal ◽  
Step Width ◽  
Automated Identification ◽  
Low Pass ◽  
Well Log Analysis

Lanning and Johnson’s paper presents the technique of Walsh transform domain low‐pass filtering as a means of enhancing transitions in well logs prior to boundary picking. They argue that existing fast means of computing the Walsh transform (fast Walsh transform algorithms) make this procedure particularly efficient. In this discussion it is shown that, for all practical cases of interest, the results of their paper can be obtained without any mention of the Walsh transform. In fact, using the Walsh transform unnecessarily increases computational complexity. Specifically, it is shown that the low‐pass sequency filtering described for obtaining a stepped version of the original signal with a given step width is equivalent to segmenting simply the signal into equal length segments and replacing all values in each segment by the segment average.

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