Quantitative Seismic Interpretation Identifies Sweet Spots in Organic-Rich Mudrocks

In this study, the authors use a quantitative seismic interpretation work flow (QSI) based on a rock-physics template in estimating the uncertainty of the geochemical properties of organic mudrocks of the Shublik formation of the Alaskan North Slope.

3D interpretation of subsurface enabled by seismic

Estimating the lateral heterogeneity of geochemical properties of organic-rich mudrocks is important for unconventional resource plays. Well-penetration data from emerging plays are sparse and so traditional geostatistical methods will not yield good results. In this study, the authors use a quantitative seismic interpretation work flow (QSI) based on a rock-physics template in estimating the uncertainty of the geochemical properties of organic mudrocks of the Shublik formation of the Alaskan North Slope. By combining the rock-physics template and the results of seismic inversion, multiple realizations of total organic content (TOC), matrix porosity, and brittleness index are generated. These parameters can be used for sweet-spot detection.


Data for physical rock parameters are generally restricted to well locations. To extend data laterally, two general directions can be taken: a data-oriented approach and a physics-oriented approach. The data-oriented approach is powerful but requires a large amount of data commonly not available in emerging areas where well penetration is scarce. Physics-oriented approaches can be used to obtain the desired parameters used in decision-making; however, the results are highly dependent on the inputs, such as TOC and hydrogen index, and these typically are not defined regionally.

The QSI is a powerful tool that can be used to estimate the lateral and vertical heterogeneity of rocks beyond wellbores. QSI combines both of the previously mentioned approaches by using well data to calibrate rock-physics models and then using statistical methods to derive relationships between rock-physics models and seismic data.

In the complete paper, the authors demonstrate a work flow to apply the QSI to organic-rich mudrocks by incorporating a constructed rock-physics template for mudrocks. Joint estimation of rock properties is used to estimate the geochemical and mechanical properties important in determining sweet spots. Multiple possible realizations of Earth models are generated to capture the nonuniqueness associated with the inversion problem.

Study Area

The Triassic Shublik source rock is the main petroleum source in the North Slope of Alaska. The organic-rich calcareous interval is interpreted to be deposited during a marine upwelling period. Lateral and vertical heterogeneity in the Shublik formation has been documented with multiple facies identified.

The study area is south of the Prudhoe Bay oil field. The area of interest spans an area of approximately 41×42 km. Two wells are available in the study area, Merak 1 and Alcor 1, both drilled in 2012. The fact that the wells lie on the edge of the seismic survey and that the distance between them is only approximately 3 km is not ideal because they might not represent all possible rock variations observed in the study area. However, the wells have rich data sets including core, traditional well logs including shear sonic, rock-evaluation data including TOC, vitrinite reflectance indicating thermal maturity, X-ray fluorescence (XRF) elemental data, and miscellaneous drilling reports.

Seismic and seismically derived data available in the study area include

  • Post-stack-time migrated stack
  • Near-angle stack with 0° to 15°
  • Mid-angle stack with angles of 15 to 30°
  • Far-angle stack with angles of 30 to 45°
  • Estimated velocity cube used in seismic migration

Rock-Physics Template

The template is constructed by a combination of differential effective media (DEM) Gassmann fluid substitution, and Backus averaging. Well data (well logs, XRF elemental data, and pyrolysis results) are used for calibration. The inputs for the template include

  • Lithological proportion
  • Matrix porosity
  • Kerogen type and amount
  • Thermal maturation
  • The outputs for the model include
  • P-impedance
  • S-impedance
  • Density

Fig. 1 illustrates the work flow. To estimate elastic properties, matrix minerals are mixed isotropically. Pore volume is inserted using DEM, and Gassmann substitution is used to fill the pores with oil. Kerogen is modeled separately as a function of thermal maturity. Kerogen nanopores are inserted using DEM, and Gassmann substitution is used to fill the nanopores with oil. The nanopore fraction is modeled as a function of thermal maturity. Kerogen solid densification is also included. The kerogen and the matrix are mixed to create a vertically transposed isotropic medium using Backus averaging.

Fig. 1—General work flow followed for constructing the low-frequency rock-physics template for organic-rich mudrocks. The effective properties of the organic component (left) and inorganic component (right) of the rock are calculated separately. Backus averaging is used to combine the two components. The organic component changes as a function of thermal maturity.


Using the calibrated rock-­physics ­template as a model, the priors of the elastic properties are constructed. Lithological proportions and matrix-­porosity priors are sampled from compositional random distribution using Dirichlet distribution. Thermal maturation and matrix porosity are sampled from uniform distribution. Because the two available wells are at the edge of the study area, it is highly likely that some intervals in the study contain different rocks from those in the wells.

Seismic Inversion

Joint seismic inversion is performed to obtain an estimate of P-impedance, S‑impedance, and density. First, seismic-to-well tie is performed using the check shots. Second, wavelets are extracted from the seismic. Next, the initial model is constructed and the seismic is inverted to obtain the seismic impedance cubes and density. This procedure used is deterministic; it is also subjective, because it requires substantial input from the geoscientist. The complete paper describes some of the choices made in the seismic inversion process and the reasoning behind them.

Property Estimation

Now that the rock-physics template is constructed, and the seismically derived elastic properties are estimated, the properties of the rocks given the seismically derived elastic properties can be estimated. In a Bayesian framework, the rock-physics template is the prior, and the seismically derived elastic properties of the Shublik formation are the data. Making certain that the seismic inversion results lie within the prior is important.

Approximate Bayesian computation is used to approximate the posterior. First, the template is sampled randomly. The template is constrained to the thermal maturity defined on the basis of an estimation from a large-scale basin and petroleum-system model. The Euclidean distance between the sampled template points and the seismic inversion results is calculated. The nearest 1% samples from the template are identified and converted to a probability density function using a softmax function. With each realization, all the petrophysical properties used as an input in the rock-physics model are obtained: matrix-lithological-components proportion, matrix pore fraction, TOC, kerogen nanopore fraction, and thermal maturity.


The quantitative seismic work flow is applied on an organic-rich mudrock interval. Using a rock-physics template that incorporates lithological components, thermal maturity, TOC, matrix porosity, and brittleness index were obtained on the seismic scale. Results show variable lithology trending south to north. Validation is needed to confirm this hypothesis. As with any QSI work flow, this case study requires expertise in geology, geophysics, and statistical analysis with emphasis on geochemistry and mudrock characterization. The authors do point out limitations and uncertainties of the proposed work flow, such as those pertaining to the rock-physics template, seismic inversion, and the property-estimation process. These limitations underscore the importance of working in multidisciplinary teams.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 197290, “Quantitative Seismic Interpretation Work Flow for Sweet-Spot Identification in Organic-Rich Mudrocks,” by Mustafa A. Al Ibrahim, Tapan Mukerji, SPE, and Allegra Hosford Scheirer, Stanford University, prepared for the 2019 SPE Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 11–14 November. The paper has not been peer reviewed.