Reducing Inversion Ambiguity by Use of Reservoir Simulation a Priori Information in Microgravity Oil-Water Flood Front Monitoring (2014)

Abstract Traditional gravimetry applications are mining/oil exploration surface gravity and formation bulk density borehole gravity logging. Large-scale reservoir saturation monitoring is a new gravimetry application. Substitution of oil or gas by water leads to density changes in large reservoir volumes, which causes time dependent subsurface and surface gravity field variations. This case study presents a complex multilayered reservoir time-lapse gravity data inversion problem. The customary bitmap approach requires many input parameters with a well-known inversion ambiguity. This ambiguity is in this work reduced by introducing a priori information obtained by biasing the inversion with history matched reservoir simulation output. A synthetic gravity data set was first generated by forward gravity modeling using the simulation saturation output from an onshore giant Middle Eastern oil field. By analyzing the simulation saturation data, the reservoir layer specific behavior of the water saturation and oil-water flood front was understood and used as a priori input in the optimized inversion algorithm used to fine-tune the predicted location of the oil-water flood front on the basis of the synthetic gravity data. Numerical examples with associated graphics demonstrate how inversion and accuracy estimates work for this data set. The proposed inversion technique will depict differences from the history matched simulation saturation and the gravity data; therefore, actual field gravity data will allow the enhancement of the reservoir simulation history match precision. The presented inversion of time-lapse gravity data demonstrates a substantial potential for the 4D microgravity. Since borehole gravity sensors are less affected by near surface changes, the borehole gravity data has significantly improved spatial resolution and much higher measured ? in the gravity signal resulting from the fluid substitution of hydrocarbons by water. In the presented inversion work, the maximum synthetic time-lapse ? gravity signal at the top reservoir was 18 times greater in magnitude compared to the predicted maximum surface time-lapse gravity signal amplitude. For microgravity to be a serious alternative for inter-well hydrocarbon saturation mapping for oil fields under waterflood, the borehole microgravity hardware development needs to be given significant R&amp;D priority to reduce the diameter of the borehole gravity tool and improve gravity meter precision for both surface and borehole sensors. Introduction Geology and reservoir engineering describe the subsurface reservoir by utilizing sparse well data. As only a very small fraction of the subsurface can be observed through cores, well logs and well production data, the inter-well reservoir characterization is very challenging, especially in heterogeneous or fractured reservoirs, where simply interpolating wellbore data is not adequate to infer fluid distribution. At present, dynamic changes between wellbore control points is only understood via matching reservoir simulation models to reproduce the acquired well data. In the Journal of Petroleum Technology (JPT) May 2011 issue, the Society of Petroleum Engineers (SPE) Research &amp; Development (R&amp;D) Committee defined the five grand R&amp;D challenges facing the oil and gas industry (Judzis et al. 2011), which included higher resolution subsurface imaging of hydrocarbons. In a follow-up JPT article, Neal and Krohn (2012) identified the most advanced technology options offering a solution to the inter-well hydrocarbon mapping problem as:3D/4D Seismic: surface, borehole and cross-well acquisition;Electromagnetic: borehole to surface and crosswell;Microgravity: borehole and surface acquisition; andNanotechnology.