Blackfoot Field Research Articles

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: a comparative case study

Accurate reservoir characterization is necessary to effectively monitor, manage, and increase production. A seismic inversion methodology using a genetic algorithm (GA) and particle swarm optimization (PSO) technique is proposed in this study to characterize the reservoir both qualitatively and quantitatively. It is usually difficult and expensive to map deeper reservoirs in exploratory operations when using conventional approaches for reservoir characterization hence inversion based on advanced technique (GA and PSO) is proposed in this study. The main goal is to use GA and PSO to significantly lower the fitness (error) function between real seismic data and modeled synthetic data, which will allow us to estimate subsurface properties and accurately characterize the reservoir. Both techniques estimate subsurface properties in a comparable manner. Consequently, a qualitative and quantitative comparison is conducted between these two algorithms. Using two synthetic data and one real data from the Blackfoot field in Canada, the study examined subsurface acoustic impedance and porosity in the inter-well zone. Porosity and acoustic impedance are layer features, but seismic data is an interface property, hence these characteristics provide more useful and applicable reservoir information. The inverted results aid in the understanding of seismic data by providing incredibly high-resolution images of the subsurface. Both the GA and the PSO algorithms deliver outstanding results for both simulated and real data. The inverted section accurately delineated a high porosity zone (>20%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>20\\%$$\\end{document}) that supported the high seismic amplitude anomaly by having a low acoustic impedance (6000–8500 m/s∗\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$*$$\\end{document} g/cc). This unusual zone is categorized as a reservoir (sand channel) and is located in the 1040–1065 ms time range. In this inversion process, after 400 iterations, the fitness error falls from 1 to 0.88 using GA optimization, compared to 1 to 0.25 using PSO. The convergence time for GA is 670,680 s, but the convergence time for PSO optimization is 356,400 s, showing that the former requires 88%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$88\\%$$\\end{document} more time than the latter.

First-break prediction in 3-D land seismic data using the dynamic time warping algorithm

SUMMARY This paper presents a new methodology to assist geophysicists in determining the first-break event in a 3-D seismic data set using the well-known technique called dynamic time warping algorithm (DTW), which is usually used to find the optimal alignment between two time-series. We used the optimal path from the cost matrix to identify the first break in the seismogram using a few picks (seeds) made by an interpreter as a reference to perform this task. Furthermore, the data were pre-conditioned by the topographic and linear moveout to improve the method’s accuracy. To demonstrate the technique’s robustness, first, we applied the methodology in a synthetic seismic data. After demonstrating the efficiency of the algorithm, we applied the aforementioned methodology in the Polo-Miranga 3-D seismic cube located in the Recôncavo sedimentary basin, Bahia-Brazil, and in the seismic data acquired from the Blackfoot field in Alberta, Canada. The high-quality results showed consistency in determining the first break in all ranges of offsets, demonstrating an alternative way to accelerate this seismic processing step. Furthermore, we compared the results obtained by the proposed methodology with an algorithm based on comparing the short-time averages with long-time averages. Finally, we performed the static correction calculation to ensure that the time distortion resulting from the terrain and the low-velocity layer was mitigated in shoot gathers and in the stacked section.

Qualitative and quantitative comparison of the genetic and hybrid genetic algorithm to estimate acoustic impedance from post-stack seismic data of Blackfoot field, Canada

SUMMARY In this study, seismic inversion is carried out using a genetic algorithm (GA) as well as a hybrid genetic algorithm (HGA) approach to optimize the objective function designed for the inversion. An HGA is a two steps coupled process, where a local optimization algorithm is applied to the best model obtained from each generation of the GA. The study aims to compare the qualitative as well as the quantitative performance of both methods to delineate the reservoir zone from the non-reservoir zone. Initially, the developed algorithm is tested on synthetic data followed by its application to real data. It is found that the HGA for synthetic data is providing more accurate and high-resolution subsurface information as compared with the conventional GA although the time taken later is less as compared with the former methods. The application to real data also shows very high-resolution subsurface acoustic impedance information. The interpretation of the impedance section shows a low impedance anomaly zone at (1055–1070) ms time interval with impedance ranging from (7500 to 9500) m s−1*g cc−1. The correlation between seismic and well data shows that the low impedance zone is characterized as a clastic glauconitic sand channel (reservoir zone). In seismic inversion using an HGA, one can delineate the areal extent of the reservoir zone from the non-reservoir zone more specifically as compared to the GA-derived impedance. The convergence time of HGA is 4.4 per cent more than GA and can be even more for larger seismic reflection data sets. Further, for a more detailed analysis of the reservoir zone and to cross-validate inverted results, an artificial neural network (ANN) is applied to data, and porosity volume is predicted. The analysis shows that the low impedance zone interpreted in inversion results are correlating with the high porosity zone found in ANN methods and confirm the presence of the glauconitic sand channel. This study is important in the aspect of qualitative as well as quantitative comparison of the performance of the GA and HGA to delineate sand channels.

Characterising sand channel from seismic data using linear programming (l1-norm) sparse spike inversion technique: a case study from offshore, Canada

In this study, a linear programming (l1-norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot Field, Alberta, Canada. The aim of study is to determine high-resolution subsurface rock properties from the low-resolution seismic data and characterise the clastic Glauconitic channel. There are many traditional post-stack seismic inversion techniques available to estimate rock properties from seismic data, but LPSSI is a relatively simple and quick to compute subsurface model that can be used for qualitative as well as quantitative interpretation. The technique is applied in two steps; first, composite traces near to well locations are extracted and inverted for acoustic impedance, and comparison with well log impedance is used to optimise the LPSSI parameters. Analysis of the composite traces indicates that the algorithm has good performance with high correlation (0.97). In the second step, LPSSI is applied to the Blackfoot seismic data to estimate the distribution of acoustic impedance in the subsurface. Analysis of inverted acoustic impedance shows a low impedance anomaly ranging from 6500 to 8500 m/s*g/cc at the 1060–1075 ms time interval, which is characterised as a clastic Glauconitic sand channel. Thereafter, to confirm the sand channel, another important rock property, porosity, is estimated in the inter-well region using multi-attribute analysis. Analysis of the porosity shows the presence of a high porosity (15–22%) zone in the 1060–1075 ms time interval which coincides with the low impedance zone and confirms the presence of the sand channel.

Use of genetic algorithm in reservoir characterisation from seismic data: A case study

In the present paper, a seismic inversion based on genetic algorithm (GA) is performed to characterise the reservoir using seismic data only from the Blackfoot field, Alberta, Canada. The algorithm is first tested on synthetically generated data to optimise the GA parameters. The error analysis between the inverted and the expected results suggested that the performance of algorithm is exceptionally satisfactory. Thereafter, the inversion is performed for real seismic data from the Blackfoot field. The seismic data is first inverted for acoustic impedance section and then it is transformed into the velocity and density sections using the relation derived from the well-log data. The interpretation of the inverted/derived results depicts a low-amplitude anomaly zone between 1055 and 1065 ms time interval, which is characterised as a reservoir. The results demonstrate the efficacy and applicability of the GA in reservoir characterisation from the seismic data alone. This study is very helpful for the offshore projects where the information about well logs are missing.

Application of LP and ML sparse spike inversion with probabilistic neural network to classify reservoir facies distribution - A case study from the Blackfoot field, Canada

Sparse-Spike inversion techniques are used to estimate distribution of acoustic impedance in inter well region, the important parameters for characterizing the reservoir facies from seismic and well log data. The purpose of sparse spike impedance inversion is to obtain high-resolution impedance profile of the subsurface from the low resolution seismic data with the integration of well log data and enhance the interpretation of the prospective zone. In the present study, two types of sparse spike inversion techniques, namely, Linear Programming (LP) sparse spike inversion and Maximum Likelihood (ML) sparse spike inversion are applied to estimate acoustic impedance from seismic data of the Blackfoot region, Alberta, Canada. The principle objective of the study is assessing the relative performance of these techniques for estimation of petrophysical parameters to identification of prospective zones in the area. Initially, the inversion methods are applied to the composite trace near to well locations and inverted for acoustic impedance and compared with the actual impedance derived from the well log data. The result demonstrates that both curves are matching with each other very well. The correlation is estimated to be 0.97 and 0.93, Synthetic relative error (SRE) 0.23 and 0.34 and Root mean square (RMS) errors are 1125 m/s*g/cc and 1205 m/s*g/cc for Linear Programming sparse spike inversion (LPSSI) and Maximum Likelihood sparse spike inversion (MLSSI), respectively. The analysis for composite traces depicts the robustness and performance of the algorithm. Thereafter, the techniques are applied to seismic volume to estimate variation of acoustic impedance in inter well regions. The analysis of inverted impedance shows a low impedance anomaly in between 1060 and 1075 ms time intervals which may be due to presence of reservoir facies (sand channel). The analyses of the inverted results reiterate that both methods work satisfactory and show variation of reservoir facies in similar way. The results found by LPSSI shows slightly higher resolution compared to the MLSSI results. Thereafter, to enhance reservoir facies more clearly, porosity is predicted in inter well region by using probabilistic neural network (PNN) technique. The result shows very high porosity (> 15%) in between 1060 and 1075 ms time interval which corroborated with the low impedance zone and confirms the presence of sand channel. The qualitatively and quantitatively analysis of inversion results suggest that the LPSSI along with PNN provides better reservoir characterization than MLSSI and PNN combination for the Blackfoot field, Alberta, Canada.

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000–8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

Spectral decomposition aids AVO analysis in reservoir characterization: A case study of Blackfoot field, Alberta, Canada

Blackfoot field, Alberta, Canada, has produced oil and gas from a Glauconitic compound incised valley-system. In this area channels can be filled with sands and/or shales. Differentiation of prospective channel sands and non-productive shales was always problematic due to the similarity in P-wave impedance of these two lithotypes. We study the spectral decomposition response to the hydrocarbons presence in the Glauconitic channel of Early Cretaceous age. From previous AVO analysis and modeling, a strong Class III AVO anomaly has been observed at the top of the porous sandstone in the upper valley, whereas shale had a very different AVO response. Furthermore, AVO inversion revealed additional information about lithology and fluid content in the channel. Our workflow starts from selecting a continuous horizon that was close and conforms to the channel interval; we then run spectral analyses for the channel area. Short Window Fourier Transform workflow could successfully image the channel's stratigraphic features and confirm results obtained from AVO analysis and inversion run on the data before being stacked. Additionally, the producing oil wells in the sand-fill channel were found to be correlating with high spectrum amplitude; while the dry wells in the shale-plugged channel fell in low amplitude anomaly.

Inversion for Thomsen’s anisotropy parameters

In order to extend seismic processing techniques to anisotropic media, it is required that we have a measure of the different anisotropy parameters. The purpose of this study is to estimate the Thomsen?s parameters, e and d, for transversely isotropic (TI) media using the shifted hyperbola NMO equation by Castle. A non-linear inversion technique has been developed to invert the Castle?s Shifted Hyperbola NMO Equation for obtaining the shift parameter. This method will be used for the estimation of these parameters over the Blackfoot field in western Canada.

Analyzing three‐component 3D vertical seismic profiling data

A three‐component 3D vertical seismic profile (VSP) was acquired over the Blackfoot oil field in Alberta, Canada. The VSP survey was recorded simultaneously with a surface seismic program. The objectives of the VSP were to develop recording logistics, data handling, and processing procedures and to determine if the 3D VSP volumes could image the glauconitic sand reservoir of the Blackfoot field.Dynamite shots from the surface seismic survey, which fell within a 2200‐m offset from the recording well, were used in the VSP analysis. The shots were recorded by a string of three‐component borehole receivers that was moved seven times, resulting in a receiver depth range of 400 to 910 m. The borehole data were processed using basic VSP processing techniques that included hodogram analysis, wavefield separation using median filters, and VSP deconvolution. The final P‐P and P‐S image volumes were obtained by VSP common‐depth point and VSP common‐conversion point stacking the upgoing wavefields followed by f‐xy deconvolution. The P‐P and P‐S images from the VSP correlate well with those from the surface seismic survey. Time slices from the VSP also indicate the trend of the sand channel of the Blackfoot field.

Integrated geological and geophysical interpretation case study, and Lamé rock parameter extractions using AVO analysis on the Blackfoot 3C‐3D seismic data, southern Alberta, Canada

Blackfoot field, southeast of Calgary, Alberta, Canada, has produced oil and gas from a Glauconitic compound incised‐valley system. The Glauconitic compound incised valley has three cycles of incision and valley fill: lower, lithic, and upper incised valleys. The upper and lower incised valleys are the main reservoirs. The geophysical interpretation of compressional PP‐seismic data resulted in the definition of the compound‐valley extent, and in the mapping of the upper and lower incised valleys. A stratigraphic well‐log template was built using the most significant lithological information and well logs. To integrate both geological and geophysical interpretations, the well log cross‐sections and corresponding depth‐converted seismic were superimposed. Furthermore, a detailed geological facies interpretation of the upper and lower incised valleys was undertaken and incorporated. A good correlation was found between the interpreted geological facies and the seismic data response. Information about the nature of the fill within the compound valley was gained from the integration of the PP‐ and PS‐wave interpretations. However, this is limited to Vp/Vs analyses on given intervals. Amplitude‐variation‐with‐offset analysis of the PP‐data was run to discriminate lithology and pore‐fluid saturates. The products of the Lamé rock parameters, incompressibility (λ) and rigidity (μ), with density (ρ) were extracted from seismic inversions for P‐ and S‐impedances. The extraction of λ ρ and μρ showed the presence of gas‐bearing porous sandstone within the Glauconitic incised‐valley system.

JointPPandPSseismic inversion

We present a case history of joint inversion of PP and PS reflection seismic data using a weighted stacking technique. Our example comes from Blackfoot Field, owned and operated by PanCanadian Petroleum, in southeastern Alberta, Canada. The exploration target at Blackfoot is a Lower Cretaceous channel system approximately 1.4 km deep (Figure 1). Figure 1. The Glauconitic channel system at Blackfoot Oil Field, Alberta, is a sequence of sand and shale filled valleys incised into Lower Cretaceous and Mississippian carbonates. The Blackfoot interpretation has an upper and lower channel that are prospective and separated by a nonporous lithic channel. These Glauconitic channels, with sand or shale fill, are found throughout the region, and, as there were many episodes of channel formation, can be stacked on top of one another. At Blackfoot, the channel interval is about 40 m thick and 100 m wide. There tends to be good porosity in an upper channel and a lower channel that are separated by a tight, lithic channel. The upper channel, where present, is usually gas-prone, while the lower channel is generally oil-prone. When the pore fluid in the channel sands is a compressible hydrocarbon instead of incompressible water, the bulk compressibility is reduced and this modifies the signature of seismic reflection data. Because pressure waves and shear waves sense different rock and pore-fluid properties, joint use of PP and PS data can provide superior lithologic discrimination. The conversion of one elastic wave, either P or S , into another upon reflection or transmission at an interface is described by the Zoeppritz equations. These equations are algebraically quite complex and it is not practical to reproduce them here. Instead, we will present useful concepts and approximate forms. (We invite the reader to visit our Web site, http://www.crewes.org, and interactively examine the equations using our …

Depth imaging by elastic wavefields—wherePmeetsS

In November 1997 the CREWES Project at the University of Calgary, with assistance from Boyd Petro‐Search Consultants and PanCanadian Petroleum, recorded a unique, high‐resolution 3-C, 2-D seismic survey at the PanCanadian‐owned Blackfoot Field some 50–55 km east of Calgary, Alberta, Canada. The producing formation is a Lower Cretaceous, cemented, glauconitic sand deposited as incised channel‐fill sediment above the Mississippian carbonates. The sandstone is about 1500 m below surface. Its thickness ranges up to 45 m. Average porosity is near 18%. Cumulative production throughout southern Alberta exceeds 200 million bls oil and 400 billion ft3 gas.

Interpreting channel sands with 3C-3D seismic data

A 3C-3D seismic survey was acquired over the Blackfoot Field (near Strathmore, Alberta, Canada) in 1995. The survey, sponsored by a group of exploration companies, was planned and conducted by the CREWES Project (Department of Geology and Geophysics, The University of Calgary) and Boyd Exploration Consultants. Simultaneously with the surface data acquisition, a five‐level 3-C downhole tool (from Western Atlas International) was deployed in a well, and a 3C-3D VSP was recorded.

Blackfoot Field, Anderson County, Texas: GEOLOGICAL NOTES

Blackfoot Field, Anderson County, Texas: GEOLOGICAL NOTES

Blackfoot Field, Anderson County, Texas: ABSTRACT

This paper presents a review of the structure, stratigraphy, and history of the Blackfoot field, Anderson County, Texas. The Blackfoot producing structure is a relatively small, faulted, elongate, domal, closure situated on an anticlinal trend which extends from northeastern Freestone County through west-central Anderson County into southeastern Henderson County and is known as the Blackfoot-Bradford Tennessee Colony trend. Productive formations include the Rodessa and Pettit limestones, and the Travis Peak sands of the Trinity group. The productive limits are not defined since the field is only partly developed. Faulting, although present at Blackfoot, is thought to be of minor significance and known faulting does not effect the local accumulation of gas and oil. Control furnished by development wells shows a typical graben fault pattern; however, the exceptional feature in Blackfoot is the termination of both faults at the point of intersection. End_of_Article - Last_Page 2068------------