An Introduction of Drilling Data Space

Abstract Traditional well planning and drilling risk management requires revisiting past experiences for a given drilling volume and it is expected that new well project evaluation requires multidisciplinary teams and plurality of data usage and access. To date, there is little integration of drilling data and mud logs into decisional data space used for well planning. Integration of drilling data and mud logs into models used for well planning allows for the data to be analyzed and used for evaluation in order to answer questions such as: will we encounter stringers? What is the expected ROP during the project? How can I de- risk the project in planning phase? We have developed a methodology to allow well planning and associated subsurface models to be created in geo-referenced drilling data space. At the heart, the method requires to build the static subsurface model using historical well trajectory, drilling data and mud log data. From this point of view the subsurface mathematical data space becomes pure drilling space where first the drilling data will populate the virtual space coordinates, allowing all otherwise standard 3D interpolation and intersect techniques to be used. Our approach provides flexibility and completeness for the data distribution as all the wells have past recorded drilling data while other sources of data may be very sparse such in the case of petrophysical or seismic data. We have tested this approach on data from one field and the methodology is robust for using historical data to populate the model and plan new wells. Using driller definitions, we have built an expedite method to detect stringers and match the new observations with sub-seismic events and petrophysical evaluations. The potential application of this method beyond what we have tested is the possibility for scale up and perform rapid comparative exercise with other information and data sets. Sources of uncertainty and possible propagation of such through drilling data space is briefly introduced. Having a historical database of drilling data in geo-referenced space gives confidence to well planning, helps the drilling team to get updated drilling information and perform risk management prior to drilling.