Green Field Development
Accurate subsurface details are crucial in greenfield oil and gas development for minimizing project risks, reducing costs, and maximizing profitability by accurately predicting reserves, optimizing well placement and drilling schedules, and designing efficient surface infrastructure. A detailed understanding of the reservoir's geology, fluid distribution and geo-mechanical behaviour enables informed decision-making, leading to more successful project. Subsurface information dictates optimal well paths and drilling parameters, crucial for successful development and preventing issues like wellbore instability or hitting unexpected geological features. Detailed subsurface knowledge informs the placement of production pads and the design of gathering systems, reducing the need for expensive redesigns or rework later in the project.
Importance of Subsurface Detail
• Exploration Efficiency: High resolution subsurface maps using seismic inversion technologies that incorporates additional information outside seismic bandwidth can reduce exploration costs and improve the accuracy of resource characterization before drilling begins.
• Risk Mitigation: Inaccurate subsurface estimates can lead to significant uncertainties in projected profit, impacting investment decisions. High-resolution subsurface models help to identify and quantify these risks, allowing for better management of project uncertainties.
• Cost Optimization: Understanding the subsurface allows for more efficient drilling and well completion operations, leading to cost reductions.
• Resource Recovery & Profitability: A detailed understanding of reservoir geometry & drive mechanisms is essential for good reserve estimation. Hence, the accurate placement of appraisal & development wells is critical to avoid costly errors
Brown Field Development
In Brown fields it is useful to screen remaining sweet spots. For example, seismic constrained porosity observations can be compared to DST performance (flow vs no flow) away from wells. Alternatively dynamic data (kvkh from PTA) can be compared with seismic derived net pay thickness map (calibrated to well results). Our extensive capability allows us to quickly integrate information across all types of Brown fields with 10's to 100's of wells. We identify high ranking infill candidates whilst eliminating areas that have been swept in very mature or declining fields. We also provide expertise for anti-collision risk drilling in significantly mature fields.
By leveraging Bayesian facies technique- joint pdfs of kappa (compressibility) and mu (shear compliance) was used to estimate discrete dolomitic pay accompanied by probability of occurrence. Using a stratigraphic framework, we can identify areas of laterally continuous dolomitic pay. These sweet spots are then used to refine placement of development wells.
Upon completing the QC of the derived maps against measured dolomite thickness from wells and dynamic kvkh data from PTA, well planning can be refined. The example shown here co-renders dolomite facies with corresponding probabilities (p>0.5) computed within the relevant stratigraphic framework.
The well path is then reviewed along section and in map view, to ensure landing within target bodies. All potential target along the well bore is subsequently ranked for value/volume.
High Resolution Models for Invisible Thin Pay
Unlike conventional inversion which cannot resolve thin/tight carbonate pay, combining high compressibility (kappa) and moderately low shear compliance from elastic inversion (WEB AVO) is able to resolve interpreted thin (10m) dolomitized pay layers. Kappa show areas of potential dolomitic pay outside the trajectory of the planned development wells, providing scope for optimization.