Estimation of Reservoir Hydraulic Property from Surface Heave Induced by Fluid Injection
Bibliographic record
Abstract
Abstract Subsurface fluid injections such as waste water disposal, waterflooding, and CO2 sequestration cause reservoir dilation. The reservoir dilation propagates to the surrounding formations and extends up to the ground surface resulting in surface heave. Previous studies have illustrated that it is possible to delineate the extent of the reservoir dilation from the surface heave measurement using inverse technique. This paper suggests that the inverse technique could be extended to estimate the growth and propagation of the reservoir dilation during the fluid injection if the surface heave is monitored continually. Then, the reservoir pressure distribution and hydraulic properties are also possibly determined from the fluid flow equations. The results obtained from the proposed technique were compared with these obtained from a fully-coupled finite element simulation of a fluid injection problem. It was found that the numerical tool could be successfully adopted to estimate an approximate value of the reservoir permeability. Introduction Subsurface fluid injections such as waste water disposal, waterflooding, and CO2 sequestration cause reservoir dilation. The reservoir dilation propagates to the surrounding formations and extends up to the ground surface resulting in surface heave. Meanwhile, the reservoir dilation changes the reservoir formation porosity which directly affects the reservoir pressure distribution and hydraulic properties. In reservoir engineering, it is critical to estimate the reservoir pressure distribution and hydraulic properties subject to subsurface fluid injections. The inverse problem of using displacements observed at the surface of reservoir formation to infer in-situ processes and volume changes within the reservoir has been taken as a noninvasive method(1–3). This paper suggests that the inverse technique could be extended to estimate the growth and propagation of the reservoir dilation during the fluid injection if the surface heave is monitored continually. Then, the reservoir pressure distribution and hydraulic properties are also possibly determined from the fluid flow equations. Inversion of Volume Strain in Reservoir from Surface Heave in 2-D Case Segall(4) proposed an equation for the vertical displacements in terms of change in pore fluid mass content in a 2-D plane strain case. Further, Nanayakkara and Wong(5) modified the equation by expressing the vertical displacements in terms of the volumetric strains. "Observation point" and "source point" are proposed and used in this method (see Figure 1). The approach is to divide the region, in which the subsurface volumetric strains occur, into a number of infinitesimal elements. Then, each element is represented by a center of dilatation (or compression) corresponding to an infinitesimal volume change (dV), which is known as a "source point". The total vertical displacement at a given surface "observation point" is obtained by summing the contribution from each source point. Accordingly, the vertical displacement at a given surface observation point, induced due to the reservoir volumetric strains, is given by: Equation (1) (Available in full paper) where a, b are the source point coordinates and the minus sign infers that the displacement direction of the surface observation point is upward in the coordinate system shown in Figure 1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".