A high resolution inversion method for fluid factor with dynamic dry- rock VP/VS ratio squared

As an important indicator parameter of fluid identification, fluid factor has always been a concern for scholars. However, when predicting Russell fluid factor or effective pore-fluid bulk modulus, it is necessary to introduce a new rock skeleton parameter which is the dry-rock VP/VS ratio squared (DVRS). In the process of fluid factor calculation or inversion, the existing methods take this parameter as a static constant, which has been estimated in advance, and then apply it to the fluid factor calculation and inversion. The fluid identification analysis based on a portion of the Marmousi 2 model and numerical forward modeling test show that, taking the DVRS as a static constant will limit the identification ability of fluid factor and reduce the inversion accuracy. To solve the above problems, we proposed a new method to regard the DVRS as a dynamic variable varying with depth and lithology for the first time, then apply it to fluid factor calculation and inversion. Firstly, the exact Zoeppritz equations are rewritten into a new form containing the fluid factor and DVRS of upper and lower layers. Next, the new equations are applied to the four parameters simultaneous inversion based on the generalized nonlinear inversion (GNI) method. The testing results on a portion of the Marmousi 2 model and field data show that dynamic DVRS can significantly improve the fluid factor identification ability, effectively suppress illusion. Both synthetic and filed data tests also demonstrate that the GNI method based on Bayesian deterministic inversion (BDI) theory can successfully solve the above four parameter simultaneous inversion problem, and taking the dynamic DVRS as a target inversion parameter can effectively improve the inversion accuracy of fluid factor. All these results completely verified the feasibility and effectiveness of the proposed method.(c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).