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Additional file 3: Supplemental Table 1. The percentage of chromosome coverage (%) by ROHs in each breed. Supplemental Table 2. Candidate genes located in genomic regions with a high frequency of ROHs. Supplemental Table 3. Pig QTLs located in genomic regions with a high frequency of ROHs. Supplemental Table 4. The summary of Sample information for each breed.

Diffusive-Time-of-Flight (DTOF), representing the travel time of pressure front propagation, has found many applications in unconventional reservoir performance analysis. The computation of DTOF typically involves upwind finite difference of the Eikonal equation and solution using the fast marching method (FMM). However, application of the finite difference based FMM to irregular grid systems remains a challenge. In this paper, we present a novel and robust method for solving the Eikonal equation using finite volume discretization and the FMM.The finite volume form of the Eikonal equation is derived by differential manipulation, volume integration and the divergence theorem. Using product rule, the differential term is first converted to the divergence form. Then volume integrals that contain divergence terms are converted to surface integrals using the divergence theorem. Consequently, the spatial coordinates are replaced by cell volumes and transmissibilities which are universal for both structured and unstructured grids in finite volume simulators. When applied with the upstream scheme, the finite volume form evolves into a set of quadratic equations, and fast marching method is implemented to solve these equations.The implementation is first validated with analytical solutions using isotropic and anisotropic models with homogeneous reservoir properties. Consistent DTOF distributions are obtained between the proposed approach and the analytical solutions. Next, the implementation is applied to unconventional reservoirs with hydraulic and natural fractures. Our approach relies on cell volumes and connections (transmissibilities) rather than the grid geometry, and thus can be easily applied to complex grid systems. For illustrative purposes, we present applications of the proposed method to embedded discrete fracture models (EDFM), dual-porosity dual-permeability models, and unstructured PEBI grids with heterogeneous reservoir properties. Visualization of the DTOF provides flow diagnostics such as evolution of the drainage volume of the wells and well interactions.The novelty of the proposed approach is its broad applicability to arbitrary grid systems and ease of implementation in commercial reservoir simulators. This makes the approach well-suited for field applications with complex grid geometry and complex well architecture.

Identification of the location and orientation of fractures and preferential flow paths using the dynamic reservoir response can provide insightful guidance for naturally fractured reservoir development and management. However, data assimilation for high-resolution fractured reservoir models using well responses is time consuming. The streamline-based technology has proven to be effective and efficient for subsurface flow modeling and inverse problems. We propose a novel and robust streamline tracing method in dual porosity dual permeability (DPDK) systems and an efficient workflow to identify fracture location in fractured reservoir models using dynamic data.In DPDK models, the matrix-fracture interactions are typically described by non-neighbor connections (NNCs) which make streamline tracing non-trivial. We use a boundary layer method to reconstruct the fluxes and avoid flux discontinuities at NNCs. The flux reconstruction allows us to trace streamlines and compute the time of flight (TOF) in DPDK models. The fracture identification workflow relies on the streamline-based analytic sensitivity computation and rapid model calibration using dynamic data. Multiple realizations of fracture distribution are initialized and calibrated using observed well responses, for example water cut and BHP. The ensemble of calibrated fracture models is then used for uncertainty analysis, and a probability map of the spatial distribution of fractures is finally generated.The power and utility of our approach are demonstrated using several applications. We first validate the streamline tracing algorithm for DPDK model by comparing its TOF with the result generated by the finite volume formulation of TOF generalized for compressible flow. Next, we validate the fracture identification workflow using a synthetic case by comparing the fracture probability map with the "true" fracture distribution. Finally, we apply our method to a DPDK model of a fractured reservoir and generate fracture probability map by calibrating multiple model realizations to well production and pressure data. The fracture probability maps serve as valuable tools to guide reservoir management and field development strategy.The novelty of this work is the newly developed streamline tracing algorithm for DPDK models and the efficient workflow to generate fracture probability maps based on dynamic data. The proposed approach is easy to implement and can be coupled with commercial simulators for field scale applications.